Chapter 5 THE MODULE FOR DETERMINING AN OBJECT S TRUE GRAY LEVELS

Size: px
Start display at page:

Download "Chapter 5 THE MODULE FOR DETERMINING AN OBJECT S TRUE GRAY LEVELS"

Transcription

1 Qian u Chapter 5. Determinin an Object s True Gray evels 3 Chapter 5 THE MODUE OR DETERMNNG AN OJECT S TRUE GRAY EVES This chapter discusses the module for determinin an object s true ray levels. To compute the true ray levels of an object of interest requires the removal of the overlappin backround effects. This problem is quite complex and takes several steps to be resolved. irst in Section 5., it will be shown that an n-object-overlappin problem can always be simplified to a two-object-overlappin problem. So the research focus turns to computin true ray levels for two-object-overlappin problem. Since there is no existin method for accomplishin this task in either the transmission or the scatter imae modalities, it was necessary to develop models that can be used to remove the backround object overlappin effects. Section 5. discusses the development of the mathematical models for removin the overlappin effects for the transmission modalities. Section 5.3 discusses the models for the forward-scatter modality. Section 5.4 discusses the models for the backscatter modality and summarizes the mathematical model development. n luae inspection, it is difficult to identify the correct object that is overlapped with the object of interest. Section 5.5 analyzes the luae inspection problem, and ives an alorithm that determines the true ray level of an object of interest in the luae environment. Section 5.6 concludes this chapter. This chapter documents this research work, which is a unique contribution to the explosive detection community.

2 Qian u Chapter 5. Determinin an Object s True Gray evels 3 5. The asic Method for Removin Overlappin Effects This section beins by illustratin the method for determinin the true ray level of an object of interest when it only overlaps with another object. t will show that an n-objectoverlappin problem can always be simplified to a two-object-overlappin problem. So bein able to determine the true ray level in a two-object-overlappin problem means the ability to determine the true ray level in any overlappin problem. iure 5.- illustrates the method for determinin the true ray level in a two-objectoverlappin problem. n this fiure, several symbols are used. Symbol Obj refers to an object. Obj is the object of interest, and Obj is the backround object that overlaps with Obj. Symbol refers to a reion in an x-ray imae. is a reion uniquely formed by Obj ; is a reion uniquely formed by Obj ; and 3 is the reion formed by Obj overlappin with Obj. Please note that ray level is used in sinular form because the discussion here assumes to be in one sensin modality rather than in all four sensin modalities. Also the sementation alorithm has semented an imae into reions with relatively uniform ray levels. Thus each reion can be characterized usin its averae ray level.

3 Qian u Chapter 5. Determinin an Object s True Gray evels 3 Obj Obj X-ray Source (b) 3 (a) Obj Obj X-ray Source (c) iure 5.- llustration of two-object-overlappin scenarios. a) Three reions are formed in the projected x-ray imae. and are formed by Obj and Obj respectively. 3 is formed by Obj overlappin with Obj. b) Obj may be in front of Obj. c) Obj may be behind of Obj.

4 Qian u Chapter 5. Determinin an Object s True Gray evels 33 The averae ray level of is the true ray level of Obj. A typical two-objectoverlappin scenario is that does not appear in an imae, and only the overlapped reion 3 and the backround object reion appear. Thus the averae ray level of cannot be directly measured. ortunately there is a fixed relationship between the ray level of 3 and the true ray levels of Obj and Obj. rom Section 5. to Section 5.4 mathematical equations are established to model this relationship for the different sensin modalities. Those mathematical equations are called overlap models. Each model allows the computation of the ray level of the overlapped reion 3 in an imain modality usin the true ray levels of Obj and Obj. Most importantly, each model, after careful manipulation, also allows the computation of the true ray level of Obj once the ray level of 3 and the true ray level of Obj are known. Usin these models, the overlappin effects are removed from the object of interest, and the true ray levels can be computed for the object of interest in all four sensin modalities. Due to x-ray physics, the relative positions of Obj to Obj makes no difference in the transmission modality. t does make difference in the either scatter modality. So there should be one model for low-enery transmission modality; one model for hih-enery transmission modality; two models for forward scatter modality; and two models for backscatter modality. To understand that all overlappin problems can be simplified to a two-objectoverlappin problem, first, a three-object-overlappin problem is examined. Assume that three objects are overlapped as seen in iure 5.-. Since is formed by Obj overlaps with Obj 3, Obj and Obj 3 toether can be viewed as one pseudo-object Obj rather than two separate objects. This pseudo-object overlaps with Obj, and it also forms a neihborin reion. The true ray level of Obj can be directly measured at reion without the knowlede of true ray levels from either Obj or Obj 3. Since the imae reion is formed by Obj overlapped Obj, by removin the overlappin effects caused by Obj, the true ray level of Obj is revealed. The three-objectoverlappin problem is thus simplified to a two-object-overlappin problem.

5 Qian u Chapter 5. Determinin an Object s True Gray evels 34 3 (a) Obj 3 Obj Obj (b) iure 5.- llustration of a three-object-overlappin problem. a) The imae reions that are formed by three overlapped objects. b) The three objects that are overlapped.

6 Qian u Chapter 5. Determinin an Object s True Gray evels 35 The simplification procedure is enerally true for any n-object-overlappin problem. When an object of interest is overlapped with (n-) objects, those (n-) objects can always be considered as one pseudo-object. The true ray level of this pseudo-object can always be measured from one of the neihborin reions. y removin the overlappin effect caused by this pseudo-object, the true ray level of the object of interest is revealed. The n-object-overlappin problem is thus simplified to a two-objectoverlappin problem. 5. Transmission Overlap Models n eneral, the method for developin an overlap mathematical model for a certain sensin modality is as follows. irst, a mathematical model is established to formulate the overlappin relationship. Each mathematical model contains undefined constants. A number of overlappin experiments was desined to obtain the data that can later be used to define values for those constants. Note that the physical interactions that are occurrin can be quite complex. However, the purpose for the model development is to compute true ray levels of object of interest in real-time. Consequently each model must be mathematically simple. efore ettin into the discussion of the development of the low-enery transmission overlap model, it is important to know the relationship between the x-ray sinal intensity and imae ray level. All the x-ray physics analysis that is used to establish the overlap models is in terms of x-ray beam intensity. However, the AS&E system can only collect x-ray imaes that are in terms of pixel ray levels. n order to find the values for the constants in those mathematical models, ray levels must be converted to x-ray intensities. n order to use the overlap models to compute the true ray levels of an object of interest, the models must be converted into equations that are in terms of ray levels. n Section 3.3 it was found that imae ray level is a linear function of x-ray sinal intensity:

7 Qian u Chapter 5. Determinin an Object s True Gray evels 36 = c (3.3-6) where is the ray level of a pixel, is the x-ray beam intensity, and c is a conversion constant. The value of c is different for different sensin modalities. So for different sensin modalities: H H H = c (5.-) = c (5.-) = c (5.-3) = c (5.-4) where c H, c, c, and c are the conversion constants for hih-enery transmission, lowenery transmission, forward scatter, and backscatter modalities respectively. Those constants need not to be solved, because they are eventually canceled out in the derivation. Also, in transmission modalities, the ray level of an incident x-ray beam is 55, thus: H c H = 55 (5.-5) c = 55 (5.-6) where H and are the intensity of the hih- and low-enery incident x-ray beams respectively. n low-enery transmission modality, when the incident x-ray beam an object, its intensity is reduced to: traverses throuh σnx = e (5.-7)

8 Qian u Chapter 5. Determinin an Object s True Gray evels 37 The attenuation coefficient e σnx of this object is computed as: σnx e = (5.-8) et us examine the two-object-overlappin problem as seen in iure 5.-. or convenience, denote the overlapped reion as, and its x-ray intensity as. The attenuation coefficients of Obj and Obj are n e σ x nx and e σ intensity at the overlapped reion can be computed as: respectively. The x-ray σn x σ nx = e e (5.-9) The attenuation coefficient n e σ x can be computed as e σ n x, and can be computed as, where is the x-ray intensity after interacts with Obj, and is the x-ray intensity after reion can also be written as interacts with Obj. So the x-ray intensity at the overlapped ( )( ) = (5.-) Since x-ray intensities cannot be directly measured but ray levels can, the above equation must be converted to a form for ray levels. So the ray level of reion becomes = = = = = = c c σ nx e c ( )( ) c ( c c )( c c ) ( c )( c ) c 55 e σ nx (5.-)

9 Qian u Chapter 5. Determinin an Object s True Gray evels 38 where and are the true ray levels of Obj and Obj respectively. This equation establishes the relationship between the ray level of the overlapped reion and the true ray levels of objects that form this reion. Knowin the true ray levels of the objects, the ray level of the overlapped reion can be computed. Knowin the ray level of the overlapped reion and the true ray level of one of the object, the true ray level of another object can be computed. Equation 5.- is derived under the assumption that the x-ray source is a monochromatic source. However the x-ray source of AS&E system is polychromatic. To account for the polychromatic x-ray source spectrum, a constant a is added to Equation 5.-. The modified equation becomes: = a (5.-) 55 Constant a is then computed usin experimental data. Experimental data are collected from three step wedes a clear plastic step wede, an alumni step wede, and a white plastic step wede. A step wede is shown at the top part of iure 5.-. Each step is treated as an individual object. The averae ray level is computed for each step in order to remove the noise in the imae. Table 5.- lists the thickness of each step for each step wede. Table 5.- lists the averae ray levels of each step. Assume the step wede shown in iure 5.- is a clear plastic step wede. The thickness of step is.6 cm; the thickness of step 3 is.8 cm; and the thickness of step 4 is.4 cm. f step is considered as Obj, step 3 is considered as Obj, then step 4 can be considered as the overlapped object formed by Obj and Obj. This is because the thickness of step 4 is equal to the thickness of step plus the thickness of step 3, and step 4 is made of the same material as step and 3. So by measurin the ray levels of step, 3, and 4, measured.,, and can be

10 Qian u Chapter 5. Determinin an Object s True Gray evels 39 A step wede + = Step Av: 5 Step 3 Av: 74 Step 4 Av: 57 iure 5.- llustration of data collection from a step wede.

11 Qian u Chapter 5. Determinin an Object s True Gray evels 4 Table 5.- Thickness of each step of each step wede Step Number Clear Plastics (cm) White Plastics (cm) Aluminium (cm) Table 5.- True ray levels of steps in low-enery transmission modality Step Number Clear Plastics White Plastics Aluminium

12 Qian u Chapter 5. Determinin an Object s True Gray evels 4 Applyin the same techniques to the steps of all three step wedes, one can et 8 sets of experimental data, and each set contains used, a can be computed as,, and. f only one set of data is a 55 = (5.-3) To minimize the error, all 8 sets of data are used to compute a. The formula used is a = n 55 n (5.-4) where n is the number of sets of data that are used for computin a. n this case, n is equal to 8. After computation, a is found to be.898. n order to determine the precision of Equation 5.-, the experimental data are collected from real-world objects as well as from the previously described step wedes. The real world objects included books, explosive simulants, Walkman cassette players, shampoo bottles, etc. The averae ray level is computed for each object. An object, such as a book, is then overlapped with another object, such as a cassette player to form an object overlapped imae reion. The averae ray level of this overlapped reion is then measured. Usin Equation 5.- and the true ray levels of objects, a ray level is computed for this overlapped reion. The error is computed usin the followin equation: a err = 55 % (5.-5)

13 Qian u Chapter 5. Determinin an Object s True Gray evels 4 Table 5.-3 ives some of the results obtained from this experiment. Column is the ray level of Obj ; column is the ray level of Obj ; column 3 is the measured ray level of the overlapped reion ; column 4 is the computed ray level of reion ; and column 5 is the errors computed usin Equation The mathematical model of Equation 5.- is quite precise in computin the ray levels for the overlapped reion. or the 4 sets of data collected from the step wedes and the real-world objects, the errors are less than 4% for all the data sets. or some data sets, the errors are less than %. Equation 5.- can only be used to predict the ray level of an overlapped imae reion. Now, this equation is manipulated so that once the ray level of the overlapped reion and the true ray level of the overlappin backround object Obj are known, the true ray level of the object of interest Obj can be correctly computed. The equation for computin the true ray level of Obj is as follows: = 55 (5.-6) a One way to verify the precision of Equation 5.-6 is to use a step wede, for example, the clear step wede as seen in iure 5.-. Step 3 can be seen as step overlaps with step. So knowin the ray level of step and 3, the true ray level of step can be computed usin Equation n iure 5.-, the measured ray level of step is 5; the computed true ray levels usin step is 9, step 3 is, step 4 is, step 5 is 3, step 6 is, step 7 is, and step 8 is 4. The verification in this case shows that the precision of Equation 5.-6 is quite hih. This is enerally true for the other data sets that were collected.

14 Qian u Chapter 5. Determinin an Object s True Gray evels 43 Table 5.-3 Computed ray levels of an overlapped reion vs. the measured ray levels for some real-world objects in low-enery transmission modality Errors a % % % % % % % % % % % % % % % % % % % % % % % % % % % %

15 Qian u Chapter 5. Determinin an Object s True Gray evels 44 The derivation process of the overlap model for the hih-enery transmission modality is exactly the same done for the low-enery transmission modality. The resultin equation is H H H H = a (5.-7) 55 where H is the true ray level of Obj, the object of interest; of Obj, the backround overlappin object. H is the true ray level H is the ray level of the overlapped reion that is formed by Obj overlappin with Obj. a H was found to be.46 usin experimental data that were collected and processed the same way as in low-enery transmission case. Table 5.-4 ives some of the results obtained from the experiment in hih-enery transmission modality. or the 4 sets of data collected from the step wedes and the real-world objects, the error of this formula is less than %. The error rate in hih-enery transmission modality is smaller than in low-enery transmission modality because hih-enery transmission imaes are less noisy than low-enery transmission imaes. To compute the true ray level of Obj, the followin equation can be used H H 55 =. (5.-8) H a H The precision of Equation 5.-8 is also verified usin a similar technique that was used in the low-enery transmission. Equation 5.-8 is quite accurate in determinin an object s true ray levels.

16 Qian u Chapter 5. Determinin an Object s True Gray evels Step Computed ray levels Measured ray level: 5 iure 5.- Results of the computed ray levels for step of a clear plastics step wede in low-enery transmission modality.

17 Qian u Chapter 5. Determinin an Object s True Gray evels 46 Table 5.-4 Computed ray levels of an overlapped reion vs. the measured ray levels for some real-world objects in hih-enery transmission modality H H H H H H Errors a % % % % % % % % % % % % % % % % % % % % % % % % % % % %

18 Qian u Chapter 5. Determinin an Object s True Gray evels orward-scatter Overlap Models The mathematical models for forward-scatter and backscatter overlap models are much more complicated than transmission overlap models. However, these formulas can still be derived in a similar manner as was employed to create transmission models. The undefined constants in the scatter overlap models can then be defined usin experimental data. The accuracy of each formula is verified usin more experimental data. n forward-scatter modality, there are two different cases when two objects are overlapped. n case, Obj is in front of Obj as seen in iure 5.- (b). n case, Obj is behind Obj as seen in iure 5.- (c). et us bein with the derivation of the mathematical formula for case from the analysis model as seen in iure The followin is a list of symbols used in the analysis model: Obj The object of interest. Obj The overlappin backround object. The intensity of the incident x-ray beam. The transmission intensity after The forward scatter intensity after The transmission intensity after The forward scatter intensity after a The transmission intensity after a The forward scatter intensity after b The sinal of scatter sinal. c The sinal of traverses throuh Obj. traverses throuh Obj. traverses throuh Obj. traverses throuh Obj. traverses throuh Obj. traverses throuh Obj. bein transmitted throuh Obj. t is still a forward bein scattered by Obj. t is a forward scatter sinal. The forward scatter intensity of the overlapped reion.

19 Qian u Chapter 5. Determinin an Object s True Gray evels 48 Obj a a b Obj c iure 5.3- Analysis model for forward-scatter modality when two objects are overlapped. This fiure shows the end view of the two objects Obj and Obj, where Obj is closer to the x-ray source than Obj.

20 Qian u Chapter 5. Determinin an Object s True Gray evels 49 This analysis model tries to resolve one issue: with knowlede of and from Obj, and and from Obj, how can the forward-scatter x-ray intensity for the overlapped reion be computed when Obj is overlapped with Obj, and Obj is closer to the x-ray source. The assumption is that reardless of the intensity and types of incident x-ray beams, the portions of the x-ray intensity that are bein transmitted and forward scattered by Obj remain constant. The portion bein transmitted can be computed as. The portion bein forward scattered can be computed as. When a beam of x-ray first traverses throuh Obj, then traverses throuh Obj, the followin process happens. The incident x-ray beam interacts with Obj, yields a transmission sinal, and a forward scatter sinal in the forward direction. The transmission sinal interacts with Obj and yields a transmission sinal a and a forward scatter sinal a. The forward scatter sinal interacts with Obj, the sinal bein transmitted when traversin throuh Obj is b, which is still a forward-scatter sinal; and the sinal bein forward scattered by Obj is c., where can be computed as a is the fraction of incident x-ray that is forward scattered. is the incident x-ray beam to Obj, and b can be computed as, where is the incident x-ray forward scatter enery to Obj, and is the fraction of the scattered sinal that is transmitted by Obj. c can be computed as scattered by Obj., where is the fraction of the scattered sinal that is

21 Qian u Chapter 5. Determinin an Object s True Gray evels 5 Thus, the combination of the sinal ( ) c b + can be computed as ( ) +, where and are two constants used to calibrate the results. The calibration is needed because the x-ray source is not an ideal parallel source, and the eometry of the forward-scatter detectors needs to be considered as well. ( ) + is used to account for the non-linear part of the sinal ( ) c b + that is inored by ( ) +. n summary,, the forward scatter intensity of the overlapped reion is the summation of a, b, and c. t can be computed as: ( ) ( ) c b a β β β β β = = + + = (5.3-) The last line of this equation is the expansion of the next to last line. Since the terms of and do not contribute much to the overall computation of, they are inored. After simplification of Equation 5.3-, the equation becomes: = (5.3-) When converted in the form of ray levels, Equation 5.3- becomes:

22 Qian u Chapter 5. Determinin an Object s True Gray evels = (5.3-3) where is the true transmission ray level of Obj ; is the true forward-scatter ray level of Obj. is the true transmission ray level of Obj. is the true forward scatter ray level of Obj. is the computed ray level of the overlapped reion. Note: the conversion factors c and c have been absorbed into,, and 3. The values of,, and 3 are computed usin the experimental data collected from the three step wedes. The method for data collection from those three step wedes is almost exactly the same as the method used in the transmission modality. The difference is that for each step of a step wede, the averae ray level in low-enery transmission modality is measured; the averae ray level in the forward-scatter modality is also measured. So each set of data is comprised by six ray levels:,,,,, and. 8 sets of those data are collected from three step wedes. Usin least-squareerror fittin method, the values of those constants are found to be =.8, =.3, and 3 =.6. iure 5.3- shows the comparison between the measured and the computed for some steps of a white plastic step wede. The errors in this case are very small. Equation works well with materials such as white plastics. What is particularly interestin is that this equation successfully predicted that the ray level decrease when the thickness of the object increases beyond a certain threshold. This prediction can be observed in iure Note: the larer the step number is, the thicker the overlapped reion.

23 Qian u Chapter 5. Determinin an Object s True Gray evels 5 5 Gray evel 5 5 Measured Computed Set Step Number number iure 5.3- Comparison between the measured ray level of the overlapped reion and the computed ray level of for some steps of a white plastic step wede in the forward scatter modality.

24 Qian u Chapter 5. Determinin an Object s True Gray evels 53 However, Equation does not work well with other materials. or some real-world objects that were tested, the computation error is reater than 5%. Some of the results are shown later in this section. There are many sources that miht contribute to this error. or example, the x-ray source is not an ideal parallel source. The detector eometry affects the collection of forward-scatter x-ray sinals. t was assumed that the fraction of the incident x-ray bein transmitted or forward scattered is constant. This may only be true in the first order approximation, but not in hiher orders. The noise of the forward scatter imaes is sinificantly larer than the transmission imaes. This may affect the precise computation of imae ray levels. The scattered radiation has a lower frequency than the transmission wavelenth and hence has less penetration power. Thus the fraction of a forward scattered sinal that is bein forward scattered should not be the same as the fraction of a transmitted sinal that is bein forward scattered. Unfortunately, there is no way that the first fraction can be directly measured or derived in the current experimental condition. One less perfect solution is to assume that those two fractions are the same. This assumption may have contributed sinificant amount of computation error to the overlap model. Due to the limitation of our equipment and fundin, it is difficult to quantify the amount of error that each of the above sources is likely to contribute. This forward scatter overlappin model can be further improved if one has the ability to determine the major source of error and to fix the model in that aspect. This mathematical model can also be improved if for different material or object thickness, different equations are used. However, refinin this model is beyond the scope of this research. t can be done if there is enouh fundin to support another 3 or 4 year of research. Usin Equation 5.3-4, the backround overlap effect can be eliminated thouh the computation may not be that accurate. Assume Obj is the object of interest, and Obj is the backround overlap object. Assume that the true transmission ray level of Obj is known; the true forward-scatter ray level of Obj is known; the forward-scatter

25 Qian u Chapter 5. Determinin an Object s True Gray evels 54 ray level of the overlapped reion is also known. The true transmission ray level of Obj can be computed usin Equation The true forward-scatter ray level of Obj can be computed as: = (5.3-4) + 3 The forward-scatter overlap model for case of the two-object-overlap problem can be derived in a similar manner. The mathematical model that results is: = (5.3-5) where =.8, =.3, and 3 =.6. The accuracy of this equation is the same as the accuracy of Equation y manipulatin this equation, the true forwardscatter ray level of Obj can be computed: = (5.3-6) + 3 Apparently, since Equation and are not very accurate in modelin forwardscatter overlap, the true ray levels computed usin Equation and are not very accurate either. Table 5.3- shows the computed true ray levels vs. the measured true ray levels for some objects of interest usin Equations and Column is the ray level of the overlapped reion formed by an object of interest and another backround object. Column is the measured true ray level of that object of interest. Column 3 is the computed true ray level of the objects of interest.

26 Qian u Chapter 5. Determinin an Object s True Gray evels 55 Table 5.3- Computed true ray levels of an object of interest vs. the measured true ray levels for some real-world objects in forward scatter modality ~ Errors % % % % % % % % % % % % % % % % % 8 3.6% % % %

27 Qian u Chapter 5. Determinin an Object s True Gray evels 56 Column 4 is the error of computation calculated usin the followin equation: ~ err = % (5.3-7) where ~ is the measured true ray level of the object of interest. y examinin Column 4 in Table 5.3-, one may find that althouh most computation errors are within %, but some of the computation errors are over %. The error is too lare for accurate true ray level computations. However, when the data in Column and the data in Column are carefully compared, one can easily see that the measured ray level at an overlapped reion is sinificantly different from the measured true ray level of the object of interest. The ray level at Column cannot be used to represent the true ray level of an object of interest. The computed true ray level shown at Column 3 is much closer to the measured true ray level shown at Column. Althouh the errors of this model are still too lare, the development of such a model represents a step forward. urther improvement to this model will not only benefit the true ray level computation, it will also directly contribute to the material characterization usin R- plane method. 5.4 ackscatter Overlap Models iure 5.4- shows the analysis model for case of the two-object-overlap problem, which is described in iure 5.-. Obj is closer to the x-ray source than Obj. The followin is a list of symbols used in the analysis model: The intensity of the backscattered sinal after The intensity of the backscattered sinal after a The intensity of the backscattered sinal after Obj. interacts with Obj. interacts with Obj. and interacts with

28 Qian u Chapter 5. Determinin an Object s True Gray evels 57 a The intensity of the backscattered sinal after a interacts with Obj. The intensity of the backscattered sinal of the overlapped reion. The assumption in this model is that reardless of the intensity and type of incident x-ray beam, the fractions of sinal bein transmitted and forward scattered by Obj remain constant; the fraction of sinal bein backscattered by Obj remain constant as well. The faction of sinal that is transmitted by Obj can be computed as. The faction of sinal that is forward scattered by Obj can be computed as. The fraction of sinal that is backscattered by Obj can be computed as. The backscatter process of two objects in an overlappin situation can be explained as follows. When the incident x-ray beam interacts with Obj, the sinal bein backscattered by Obj is ; the sinal bein transmitted is ; and the sinal bein forward scattered is. The incident x-ray to Obj is ( ) +. The sinal bein backscattered by Obj is a. a becomes the incident x-ray to Obj. The sinal bein transmitted and forward scattered is ( ) a +. a. So the total backscattered sinal is equal to Sinal a can be computed as the summation of a and a, where is the fraction of a that is bein transmitted by Obj, and bein forward scattered by Obj. is the fraction of a that is Sinal can be computed as ( ) a +, where ( ) + is the incident sinal to Obj, and is the fraction of sinal bein backscattered by Obj.

29 Qian u Chapter 5. Determinin an Object s True Gray evels 58 Obj a a Obj iure 5.4- Analysis model for backscatter modality when two objects are overlapped. This fiure shows the end view of Obj and Obj, where Obj is the object of interest, and is closer to the x-ray source than Obj.

30 Qian u Chapter 5. Determinin an Object s True Gray evels 59 Sinal, the backscatter sinal of the overlapped reion can be computed as the summation of ( ) a +. Now the mathematical model can be written as follows: = = = = β a a + a ( + ) + ( + ) ( ) + β + β ( ) 3 (5.4-) Due to system noise and some other factors, the results computed for the sinal backscattered by Obj need some calibration. and are the two constants used to calibrate the results. Row four of this equation is the expansion of row three. Equation 5.4- is then converted in the form of ray levels. The conversion factors c, c, and c are absorbed into,, and 3. The equation can then be written as: ( ) + ( ) = (5.4-) Usin a manner similar to both transmission and forward scatter model development, 8 sets of data were collected from the three step wedes. Each set of data contains 9 ray levels. or Obj, the ray levels include the true transmission ray level ; the true forward-scatter ray level ; and the true backscatter ray level. or Obj, the ray levels include the true transmission ray level ; the true forward-scatter ray level ; and the true backscatter ray level. or the overlapped reion, the ray levels include the true transmission ray level ; the true forward-scatter ray level ; and the true backscatter ray level. Usin this data the constants,,

31 Qian u Chapter 5. Determinin an Object s True Gray evels 6 and 3 can be determined usin a least-square method. They are found to be =.476, =-.639, and 3 =.38. iure 5.4- shows the comparison between the measured and the computed for some steps of a white plastic step wede. The errors in this case are extremely small; but this is not enerally true for many other objects that were tested. n some cases, Equation 5.4- has computation errors that are reater than %. Some of the computation results are shown later in this section. The sources of error are basic the same as in the forward-scatter modality. n addition, the computation of true ray level in backscatter modality relies on the knowlede of true ray level in forward scatter modality. Since no accurate true ray level in forward scatter modality can be calculated, the true ray level in backscatter modality cannot be accurate calculated. The solutions to improve this model are also the same as in the forward-scatter modality. Assume Obj is the object of interest, and Obj is its overlappin backround object. After manipulatin Equation 5.4-, the followin equation is used for compute the true backscatter ray level of Obj for case of the two-object-overlappin problem: ( + ) 3 = (5.4-3) Assume now Obj is further to the x-ray source than Obj. This is case of the twoobject-overlappin problem, as seen in iure 5.- (c). Usin similar manner, the equation for computin the true backscatter ray level of Obj can be derived. The equation is as follows: = (5.4-4) + + 3

32 Qian u Chapter 5. Determinin an Object s True Gray evels 6 5 Gray evel 5 5 Measured Computed Set Number Step number iure 5.4- Comparison between the measured ray level of the overlapped reion and the computed ray level of for some steps of a white plastic step wede in the forward-scatter modality.

33 Qian u Chapter 5. Determinin an Object s True Gray evels 6 Since the mathematical overlap models for backscatter modality are not very accurate, the true backscatter ray levels that are computed usin Equation and are not very accurate either. Table 5.4- shows some computation results usin the backscatter overlappin models. Column is the measured ray level of the overlapped reion that is formed by an object of interest and its backround object. Column is the measured true ray level of an object of interest. Column 3 is the computed true ray level of an object of interest. Column 4 is the computation error that is calculated usin the followin equation: ~ err = % (5.4-5) where ~ is the measured true ray level of the object of interest. Most of the computation errors are over %. However, most of the errors may have been caused by not knowin the accurate true ray levels in forward scatter modality. t is author s belief that if the accurate true ray level in forward scatter modality can be computed, the error of the backscatter overlap model should be less than %. n summary, from Section 5. to Section 5.4, the discussion has focused on developin models for the two-object-overlap problems. There is a model for each sensin modality. Each model is first derived usin mathematical formulas with undefined constants. The values of those constants are then computed usin experimental data collected from the three step wedes. The accuracy of each model is then verified usin real-world objects. The transmission overlap models work quite precise. The forward scatter and backscatter overlap models need further refinement, since the scatter models are just a st order approximation. However, to refine those models is beyond the scope of this study; it can be done, but would take some considerable effort.

34 Qian u Chapter 5. Determinin an Object s True Gray evels 63 Table 5.4- Computed true ray levels of an object of interest vs. the measured true ray levels for some real-world objects in backscatter modality ~ Errors % % % % % % % % % % % % %

35 Qian u Chapter 5. Determinin an Object s True Gray evels The Alorithm for Determinin the Object s True Gray evels n this section, the alorithm for computin the true ray levels of an object of interest is discussed in detail. irst, a brief introduction is iven here as the backround to the alorithm development. As discussed earlier in Section 4.4, an object of interest Obj is more likely to be semented into several different reions in bl m, for example,, etc.; but Obj is more likely to be semented into one object in bl m Obj. bl m and bl m Obj are perfectly spatially reistered. f a reion in bl m have 7% of its pixels belonin to Obj, this reion should be part of Obj. Usin this method, and other reions that belon to Obj are identified and rouped. n other words, semented labeled components in bl m can be referred as reions, and each component is denoted by. Semented labeled components in bl m Obj can be referred as objects, and each component is denoted by Obj. or each reion, an object Obj can always be found where Obj. t is impossible to correctly resolve the overlap problem since one can never know from a -D imae whether overlap occurs or not. The principle of this alorithm is to apply some exterior criteria to the imae in order to determine the true ray level of an object of interest. The alorithm development is concentrated on the true ray level computation in the transmission modalities due to three important considerations. irst, the accuracy of the forward scatter and backscatter modalities still need some improvement, so it is impossible in the current situation to create an alorithm that can accurately calculate true ray levels in either of the scatter modality usin those models. Second and most importantly, if this alorithm works in the transmission modalities, just by usin more accurate scatter overlap models, the true ray levels can be easily computed in scatter modalities. Third, althouh the scatter data is missin, the dualenery transmission data computed usin this alorithm at least allows one to distinuish oranic materials from inoranic materials.

36 Qian u Chapter 5. Determinin an Object s True Gray evels 65 Knowin only the models for eliminatin the backround effects will not allow one to correctly compute the true ray levels of an object of interest. This is because the luae inspection problem overlappin situations are typically quite complex. One such example is iven in iure n iure 5.5- (a), two reions are observed in a -D x-ray imae. Those two reions may be formed by two objects that are placed side-byside as seen in iure 5.5- (b) or by two objects that are overlapped as seen in iure 5.5- (c). ein able to correctly interpret such kinds of scenarios is crucial towards the computation of true ray levels of an object of interest. Another example is that in a ba imae, an object of interest is often surrounded by many neihborin reions. ein able to determine the correct neihborin reion that represents the backround object is another problem that needs to be correctly resolved. The methods that are used to revolve those issues are discussed in this section. These methods are implemented in the procedure true_l(). The principle of computin true ray levels is to find a special neihborin reion to an object of interest, and use this neihborin reion s ray level information to compute the true ray level of the object of interest. This special reion is a reion that is most likely to be part of the object that overlaps with the object of interest. As discussed in Section 4.3, objects in a ba can enerally be classified into two cateories: textile objects and solid objects. Textile objects are objects without constant shape. Solid objects are objects with constant shape. Explosives includin plastic explosives are considered as solid objects. Consequently, the objects of interest for this imae-processin system are solid objects. Now usin these concepts, the typical object layout in a ba is analyzed. Problems that miht prevent the computation of the true ray levels of an object are identified. Solutions to those problems are presented.

37 Qian u Chapter 5. Determinin an Object s True Gray evels 66 (a) Obj Obj Obj (b) (c) Obj iure 5.5- nterpretation of an imae scenario. The imae scenario shows in a) in a one-view imae may be interpreted as two objects are placed side by side as seen in b), or Obj is the backround object of Obj as seen in c).

38 Qian u Chapter 5. Determinin an Object s True Gray evels 67 The typical object layout in luae is shown in iure The left drawin in this fiure is the side view of a ba, and the riht drawins represent end views of the ba. The side view is the view from which the AS&E system would collect imaes. The end view is the view that one may observe from the travelin direction of the ba; the end view is used to illustrate the overlappin situations. n a ba, the ba covers or sides always appear. So every object of interest will be at least overlap with those ba covers. n most cases, people stuff their luae with towels, socks, and clothes, all of which are textile objects. So an object of interest will also overlap with these textile objects as well. However, when solid objects overlap with textile objects, in many cases, the textile objects will not sinificantly contribute to the overlapped reions. They may cause or 3 ray level variations. Consider that the noise of the system may cause up to 7 ray level variations, those effects caused by textile objects can enerally be inored. n case 3, an object of interest is overlapped with another solid object. The development of true_l() is based on handlin the object layouts shown in this. The inputs to routine true_l() are four perfectly reistered imaes: m Smth, H m Smth, bl m, and bl m Obj. or convenience, the labeled components in reions and the labeled components in bl m Obj are called objects. bl m are called Since explosives are considered as solid objects, and solid objects are usually semented into reions larer than 4 pixels in pixels are considered by true_l(). bl m, only reions with size larer than 4 Symbol Obj always represents the object of interest. n a low-enery transmission imae, a reion of interest, where Obj, may represent a situation where an object of interest Obj only overlaps with the ba covers and other textile objects, as seen in case of iure n this case,, the true ray level of Obj can be determined if the overlap effects caused by the ba covers and the textile objects are removed.

39 Qian u Chapter 5. Determinin an Object s True Gray evels 68 container cover textile objects solid objects 3 END VEW SDE VEW solid objects 3 iure 5.5- llustration of commonly seen object layout in a ba. The left raph is a side view imae, and the riht three raphs are three typical object layouts. ayout type one is when only some textile objects appear at a reion. ayout type two is that a solid object is overlapped with some textile objects. ayout type three is that a solid object is overlapped with some other solid objects, and those solid objects are overlapped with some textile objects.

40 Qian u Chapter 5. Determinin an Object s True Gray evels 69 One valid assumption is that the overlappin effects caused by the ba covers are the same everywhere in a ba. f the reion where only ba covers are found, the ray level of this reion can then be used to remove the effects caused by the ba covers. Denote this reion as Cover, and the ray level of this reion as Cover. Cover should be the brihtest reion in a low-enery transmission imae. Knowin the averae ray level of reion,, and the true ray level of Obj, Cover, the true ray level of Obj, can then be computed usin Equation This computation basically inores the effects caused by the textile objects that are inserted between the solid objects and the ba covers., However, besides overlappin with the ba covers and other textile objects, the reion of interest may also be formed by Obj overlappin with another solid object Obj besides those ba covers and some textile objects as seen in case 3 of iure To compute the true ray level of Obj,, and the ray level of a neihborin reion needs to know. Reion is the reion that belons to Obj. Part of Obj overlaps with the object of interest Obj that forms ; part of Obj only overlaps with the ba covers and some textile objects that forms. Reion should be one of the neihborin reions of. t is very difficult to determine which neihborin reion of is. Some of the neihborin reions are eliminated from the candidate list because they cannot be. Reion should always be brihter than because Obj, where Obj, forms the reion of. n the transmission modality, an overlapped reion should always be darker than the object that forms this reion. So if a neihborin reion is darker than reion, it should be eliminated from the candidate list. Reion should also have some percentae of common boundaries with. f the common boundary between a candidate reion and is less than 5% of the perimeter of, it is also unlikely that this reion is a candidate for. Hence it should be eliminated from the candidate list. n addition, the candidate true ray level computed usin Cover is also added to the list. After reion elimination usin these conditions, the number of

41 Qian u Chapter 5. Determinin an Object s True Gray evels 7 candidate reions should be around to 4. A list of candidate true ray levels of is computed usin and the ray levels of those candidate neihborin reions. As we know that Obj. The next oal is to find the true ray level of Obj. All reions, for example,, etc., that belon to Obj can be found usin the method mentioned at the beinnin of this section. After all such reions have been identified, a list of candidate true ray levels for Obj is created. t includes all the candidate true ray levels of all the reions that belon to Obj. The true ray level Obj is the candidate ray level that occurs with the hihest frequency in the list. n hih-enery transmission modality, the procedure for determinin the true ray level of Obj, H, is exactly the same as in low-enery transmission modality. Note: the brihtest reion in the low-enery transmission imae should also be the brihtest reion in the hih-enery transmission imae. Althouh this alorithm was not implemented in the forward scatter and backscatter modalities, the procedure for determinin the true ray levels of Obj, and, are no different than in either the low- or hih-enery transmission modality. Once those scatter models are refined, this alorithm can easily be modified to handle the computation in all four sensin modalities. The complete procedure in transmission modalities is described as follows: Procedure true_l(). Compute the size and boundary lenth of each reion in bl m.. or each reion in bl m, compute the averae ray level of its correspondin reion in 3. ind the brihtest reion of m Smth. m Smth that is at least 4 pixel in size.

42 Qian u Chapter 5. Determinin an Object s True Gray evels 7 4. or a reion in bl m, use the brihtest reion toether with all selected neihbors of to compute a list of possible true ray levels for in lowenery transmission modality. A selected neihbor should be brihter than ; and the common boundary between the neihbor and should be reater than 5% of the perimeter of. 5. Repeat step 4 for all reions in 6. or an object Obj in reions in bl m. Obj m with at least 4 pixels in size, determine all the bl m that belon to Obj. 7. The candidate true ray levels for an object Obj in candidate true ray levels of reions that belon to Obj. Obj m include all the 8. The true ray level for an object Obj in Obj m is the one that occurs the most frequent in the candidate list. 9. Repeat step 6 to 8 for all objects in Obj m.. Repeat step to 9 to compute the true ray levels for all reions in H m Smth. Procedure true_l() reports a list of solid objects alon with their true ray levels in lowand hih-enery transmission modalities. A typical report format is as follows: Object Number True ray level in m Smth True ray level in H m Smth Note that the object number refers to the label used in Obj m.

43 Qian u Chapter 5. Determinin an Object s True Gray evels Chapter Summary n this chapter, the development of the module for determinin an object s true ray levels is discussed. The development of this module was done in two staes. At the first stae, overlap models are developed for each of the different sensin modalities. The hih-enery and low-enery overlap models are quite precise in determinin an object s true ray levels. Althouh the forward-scatter and backscatter overlap models have not achieved the needed computation precision, they have sinificantly improved one s ability to compute the true ray levels in those two sensin modalities. urther improvement to those two models can be done with enouh fundin and additional research time. An alorithm is developed for computin the true ray levels of an object of interest for the luae inspection problem. This alorithm uses the overlap models and concepts like textile and solid objects in performin its analysis. The true ray level computation is focused on the transmission modalities. Once the scatter overlap models are refined, they can be easily added to the alorithm for computin true ray levels in those scatter modalities.

SCALE SELECTIVE EXTENDED LOCAL BINARY PATTERN FOR TEXTURE CLASSIFICATION. Yuting Hu, Zhiling Long, and Ghassan AlRegib

SCALE SELECTIVE EXTENDED LOCAL BINARY PATTERN FOR TEXTURE CLASSIFICATION. Yuting Hu, Zhiling Long, and Ghassan AlRegib SCALE SELECTIVE EXTENDED LOCAL BINARY PATTERN FOR TEXTURE CLASSIFICATION Yutin Hu, Zhilin Lon, and Ghassan AlReib Multimedia & Sensors Lab (MSL) Center for Sinal and Information Processin (CSIP) School

More information

Iterative Single-Image Digital Super-Resolution Using Partial High-Resolution Data

Iterative Single-Image Digital Super-Resolution Using Partial High-Resolution Data Iterative Sinle-Imae Diital Super-Resolution Usin Partial Hih-Resolution Data Eran Gur, Member, IAENG and Zeev Zalevsky Abstract The subject of extractin hih-resolution data from low-resolution imaes is

More information

Performance study of a fan beam collimator for a multi- modality small animal imaging device

Performance study of a fan beam collimator for a multi- modality small animal imaging device Performance study of a fan beam collimator for a multi- modality small animal imain device ASM SABBIR AHMED 1 Wolfrad Semmler 2 Jor Peter 2 1 University of Saskatchewan Saskatoon Canada & 2 German Cancer

More information

Chapter - 1 : IMAGE FUNDAMENTS

Chapter - 1 : IMAGE FUNDAMENTS Chapter - : IMAGE FUNDAMENTS Imae processin is a subclass of sinal processin concerned specifically with pictures. Improve imae quality for human perception and/or computer interpretation. Several fields

More information

Texture Un mapping. Computer Vision Project May, Figure 1. The output: The object with texture.

Texture Un mapping. Computer Vision Project May, Figure 1. The output: The object with texture. Texture Un mappin Shinjiro Sueda sueda@cs.ruters.edu Dinesh K. Pai dpai@cs.ruters.edu Computer Vision Project May, 2003 Abstract In computer raphics, texture mappin refers to the technique where an imae

More information

CAM Part II: Intersections

CAM Part II: Intersections CAM Part II: Intersections In the previous part, we looked at the computations of derivatives of B-Splines and NURBS. The first derivatives are of interest, since they are used in computin the tanents

More information

GEODESIC RECONSTRUCTION, SADDLE ZONES & HIERARCHICAL SEGMENTATION

GEODESIC RECONSTRUCTION, SADDLE ZONES & HIERARCHICAL SEGMENTATION Imae Anal Stereol 2001;20:xx-xx Oriinal Research Paper GEODESIC RECONSTRUCTION, SADDLE ZONES & HIERARCHICAL SEGMENTATION SERGE BEUCHER Centre de Morpholoie Mathématique, Ecole des Mines de Paris, 35, Rue

More information

Bus-Based Communication Synthesis on System-Level

Bus-Based Communication Synthesis on System-Level Bus-Based Communication Synthesis on System-Level Michael Gasteier Manfred Glesner Darmstadt University of Technoloy Institute of Microelectronic Systems Karlstrasse 15, 64283 Darmstadt, Germany Abstract

More information

Accurate Power Macro-modeling Techniques for Complex RTL Circuits

Accurate Power Macro-modeling Techniques for Complex RTL Circuits IEEE VLSI Desin Conference, 00, pp. 35-4 Accurate Power Macro-modelin Techniques for Complex RTL Circuits Nachiketh R. Potlapally, Anand Rahunathan, Ganesh Lakshminarayana, Michael S. Hsiao, Srimat T.

More information

A Scene Text-Based Image Retrieval System

A Scene Text-Based Image Retrieval System A Scene Text-Based Imae Retrieval System Thuy Ho Faculty of Information System University of Information Technoloy Ho Chi Minh city, Vietnam thuyhtn@uit.edu.vn Noc Ly Faculty of Information Technoloy University

More information

Robust Color Image Enhancement of Digitized Books

Robust Color Image Enhancement of Digitized Books 29 1th International Conference on Document Analysis and Reconition Robust Color Imae Enhancement of Diitized Books Jian Fan Hewlett-Packard Laboratories, Palo Alto, California, USA jian.fan@hp.com Abstract

More information

Reducing Network Cost of Many-to-Many Communication in Unidirectional WDM Rings with Network Coding

Reducing Network Cost of Many-to-Many Communication in Unidirectional WDM Rings with Network Coding 1 Reducin Network Cost of Many-to-Many Communication in Unidirectional WDM Rins with Network Codin Lon Lon and Ahmed E. Kamal, Senior Member, IEEE Abstract In this paper we address the problem of traffic

More information

Learning Deep Features for One-Class Classification

Learning Deep Features for One-Class Classification 1 Learnin Deep Features for One-Class Classification Pramuditha Perera, Student Member, IEEE, and Vishal M. Patel, Senior Member, IEEE Abstract We propose a deep learnin-based solution for the problem

More information

Probabilistic Gaze Estimation Without Active Personal Calibration

Probabilistic Gaze Estimation Without Active Personal Calibration Probabilistic Gaze Estimation Without Active Personal Calibration Jixu Chen Qian Ji Department of Electrical,Computer and System Enineerin Rensselaer Polytechnic Institute Troy, NY 12180 chenji@e.com qji@ecse.rpi.edu

More information

Enhancement of Camera-captured Document Images with Watershed Segmentation

Enhancement of Camera-captured Document Images with Watershed Segmentation Enhancement of Camera-captured Document Imaes with Watershed Sementation Jian Fan ewlett-packard aboratories jian.fan@hp.com Abstract Document imaes acquired with a diital camera often exhibit various

More information

A Scene Text-Based Image Retrieval System

A Scene Text-Based Image Retrieval System A Scene Text-Based Imae Retrieval System ThuyHo Faculty of Information System University of Information Technoloy Ho Chi Minh city, Vietnam thuyhtn@uit.edu.vn Noc Ly Faculty of Information Technoloy University

More information

Chapter 4 Imaging Lecture 18

Chapter 4 Imaging Lecture 18 Chapter 4 Imain Lecture 18 d (110) Class Announcement Term Project presentation: startin at :03 PM, Monday, Nov. 17, 08 in CHE 10 Presentation time: 10 min./person Submission: submit a PDF file of your

More information

Reducing network cost of many-to-many communication in unidirectional WDM rings with network coding

Reducing network cost of many-to-many communication in unidirectional WDM rings with network coding Reducin network cost of many-to-many communication in unidirectional WDM rins with network codin Lon Lon and Ahmed E. Kamal Department of Electrical and Computer Enineerin, Iowa State University Email:

More information

Affinity Hybrid Tree: An Indexing Technique for Content-Based Image Retrieval in Multimedia Databases

Affinity Hybrid Tree: An Indexing Technique for Content-Based Image Retrieval in Multimedia Databases Affinity Hybrid Tree: An Indexin Technique for Content-Based Imae Retrieval in Multimedia Databases Kasturi Chatterjee and Shu-Chin Chen Florida International University Distributed Multimedia Information

More information

Development and Verification of an SP 3 Code Using Semi-Analytic Nodal Method for Pin-by-Pin Calculation

Development and Verification of an SP 3 Code Using Semi-Analytic Nodal Method for Pin-by-Pin Calculation Journal of Physical Science and Application 7 () (07) 0-7 doi: 0.765/59-5348/07.0.00 D DAVID PUBLISHIN Development and Verification of an SP 3 Code Usin Semi-Analytic Chuntao Tan Shanhai Nuclear Enineerin

More information

Image features extraction using mathematical morphology

Image features extraction using mathematical morphology Imae features extraction usin mathematical morpholoy Marcin Iwanowski, Sławomir Skoneczny, Jarosław Szostakowski Institute of Control and Industrial Electronics, Warsaw University of Technoloy, ul.koszykowa

More information

Parameter Estimation for MRF Stereo

Parameter Estimation for MRF Stereo Parameter Estimation for MRF Stereo Li Zhan Steven M. Seitz University of Washinton Abstract This paper presents a novel approach for estimatin parameters for MRF-based stereo alorithms. This approach

More information

Practical training Inga Kindermann; Dominik Haeussler

Practical training Inga Kindermann; Dominik Haeussler liht interference Materials: Laserpointer mountin material diffraction ratin with 40 slits per centimetre, CD-ROM (and ), cardboard security advise: Never let the direct beam of a laser hit your eyes!

More information

B15 Enhancement of Linear Features from Gravity Anomalies by Using Curvature Gradient Tensor Matrix

B15 Enhancement of Linear Features from Gravity Anomalies by Using Curvature Gradient Tensor Matrix B5 Enhancement of Linear Features from Gravity Anomalies by Usin Curvature Gradient Tensor Matrix B. Oruç* (Kocaeli University) SUMMARY In this study, a new ede enhancement technique based on the eienvalues

More information

Protection of Location Privacy using Dummies for Location-based Services

Protection of Location Privacy using Dummies for Location-based Services Protection of Location Privacy usin for Location-based Services Hidetoshi Kido y Yutaka Yanaisawa yy Tetsuji Satoh y;yy ygraduate School of Information Science and Technoloy, Osaka University yyntt Communication

More information

WAVELENGTH Division Multiplexing (WDM) significantly

WAVELENGTH Division Multiplexing (WDM) significantly IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 25, NO. 6, AUGUST 27 1 Groomin Multicast Traffic in Unidirectional SONET/WDM Rins Anuj Rawat, Richard La, Steven Marcus, and Mark Shayman Abstract

More information

COMPLETED LOCAL DERIVATIVE PATTERN FOR ROTATION INVARIANT TEXTURE CLASSIFICATION. Yuting Hu, Zhiling Long, and Ghassan AlRegib

COMPLETED LOCAL DERIVATIVE PATTERN FOR ROTATION INVARIANT TEXTURE CLASSIFICATION. Yuting Hu, Zhiling Long, and Ghassan AlRegib COMPLETED LOCAL DERIVATIVE PATTERN FOR ROTATION INVARIANT TEXTURE CLASSIFICATION Yutin Hu, Zhilin Lon, and Ghassan AlReib Multimedia & Sensors Lab (MSL) Center for Sinal and Information Processin (CSIP)

More information

Efficient Generation of Large Amounts of Training Data for Sign Language Recognition: A Semi-automatic Tool

Efficient Generation of Large Amounts of Training Data for Sign Language Recognition: A Semi-automatic Tool Efficient Generation of Lare Amounts of Trainin Data for Sin Lanuae Reconition: A Semi-automatic Tool Ruiduo Yan, Sudeep Sarkar,BarbaraLoedin, and Arthur Karshmer University of South Florida, Tampa, FL,

More information

CONTRAST COMPENSATION FOR BACK-LIT AND FRONT-LIT COLOR FACE IMAGES VIA FUZZY LOGIC CLASSIFICATION AND IMAGE ILLUMINATION ANALYSIS

CONTRAST COMPENSATION FOR BACK-LIT AND FRONT-LIT COLOR FACE IMAGES VIA FUZZY LOGIC CLASSIFICATION AND IMAGE ILLUMINATION ANALYSIS CONTRAST COMPENSATION FOR BACK-LIT AND FRONT-LIT COLOR FACE IMAGES VIA FUZZY LOGIC CLASSIFICATION AND IMAGE ILLUMINATION ANALYSIS CHUN-MING TSAI 1, ZONG-MU YEH 2, YUAN-FANG WANG 3 1 Department of Computer

More information

A NEW METHOD FOR EXTRACTING 3D SOLID MODELS OF OBJECTS USING 2D TECHNICAL DRAWINGS

A NEW METHOD FOR EXTRACTING 3D SOLID MODELS OF OBJECTS USING 2D TECHNICAL DRAWINGS Mathematical and Computational Applications, Vol. 12, No. 1, pp. 31-39, 2007. Association for Scientific Research A NEW METHOD FOR EXTRACTING 3D SOLID MODELS OF OBJECTS USING 2D TECHNICAL DRAWINGS İrahim

More information

The Role of Switching in Reducing the Number of Electronic Ports in WDM Networks

The Role of Switching in Reducing the Number of Electronic Ports in WDM Networks 1 The Role of Switchin in Reducin the Number of Electronic Ports in WDM Networks Randall A. Berry and Eytan Modiano Abstract We consider the role of switchin in minimizin the number of electronic ports

More information

HCE: A New Channel Exchange Scheme for Handovers in Mobile Cellular Systems

HCE: A New Channel Exchange Scheme for Handovers in Mobile Cellular Systems 129 HCE: A New Channel Exchane Scheme for Handovers in Mobile Cellular Systems DNESH K. ANVEKAR* and S. SANDEEP PRADHAN Department of Electrical Communication Enineerin ndian nstitute of Science, Banalore

More information

Main Menu. Summary. Introduction

Main Menu. Summary. Introduction Imain diffraction points usin the local imae matrix in prestack miration Xiaosan Zhu* 1,2, Ru-Shan Wu 1 1 Department of Earth & Planetary Sciences, University of California, Santa Cruz, CA 9564 2 Department

More information

Grooming Multicast Traffic in Unidirectional SONET/WDM Rings

Grooming Multicast Traffic in Unidirectional SONET/WDM Rings 1 Groomin Multicast Traffic in Unidirectional SONET/WDM Rins Anuj Rawat, Richard La, Steven Marcus and Mark Shayman Abstract In this paper we study the problem of efficient roomin of iven non-uniform multicast

More information

A Web Architecture for progressive delivery of 3D content

A Web Architecture for progressive delivery of 3D content A Web Architecture for proressive delivery of 3D content Efi Foel Enbaya, Ltd. Daniel Cohen-Or Λ Tel Aviv University Revital Ironi Enbaya, Ltd. Tali Zvi Enbaya, Ltd. Enbaya, Ltd. y (a) (b) (c) Fiure 1:

More information

A Nearest Neighbor Method for Efficient ICP

A Nearest Neighbor Method for Efficient ICP A Nearest Neihbor Method or Eicient ICP Michael Greenspan Guy Godin Visual Inormation Technoloy Group Institute or Inormation Technoloy, National Research Council Canada Bld. M50, 1500 Montreal Rd., Ottawa,

More information

Learning Bayesian Networks from Inaccurate Data

Learning Bayesian Networks from Inaccurate Data Learnin Bayesian Networks from Inaccurate Data A Study on the Effect of Inaccurate Data on Parameter Estimation and Structure Learnin of Bayesian Networks Valerie Sessions Marco Valtorta Department of

More information

Edgebreaker: Connectivity compression for triangle meshes Jarek Rossignac GVU Center, Georgia Institute of Technology

Edgebreaker: Connectivity compression for triangle meshes Jarek Rossignac GVU Center, Georgia Institute of Technology 1999 IEEE. Reprinted, with permission from IEEE Transactions onvisualization and Computer Graphics, Vol. 5, No. 1, 1999 Edebreaker: Connectivity compression for trianle meshes Jarek Rossinac GVU Center,

More information

Efficient Generation of Large Amounts of Training Data for Sign Language Recognition: A Semi-Automatic Tool

Efficient Generation of Large Amounts of Training Data for Sign Language Recognition: A Semi-Automatic Tool Efficient Generation of Lare Amounts of Trainin Data for Sin Lanuae Reconition: A Semi-Automatic Tool Ruiduo Yan, Sudeep Sarkar, Barbara Loedin, and Arthur Karshmer University of South Florida, Tampa,

More information

Optimal design of Fresnel lens for a reading light system with. multiple light sources using three-layered Hierarchical Genetic.

Optimal design of Fresnel lens for a reading light system with. multiple light sources using three-layered Hierarchical Genetic. Optimal desin of Fresnel lens for a readin liht system with multiple liht sources usin three-layered Hierarchical Genetic Alorithm Wen-Gon Chen, and Chii-Maw Uan Department of Electrical Enineerin, I Shou

More information

Edgebreaker: Connectivity compression for triangle meshes

Edgebreaker: Connectivity compression for triangle meshes J. Rossinac GVU Technical Report GIT-GVU-98-35 (revised version of GIT-GVU-98-7) pae Edebreaker: Connectivity compression for trianle meshes Jarek Rossinac GVU Center, Georia Institute of Technoloy Abstract

More information

Module. Sanko Lan Avi Ziv Abbas El Gamal. and its accompanying FPGA CAD tools, we are focusing on

Module. Sanko Lan Avi Ziv Abbas El Gamal. and its accompanying FPGA CAD tools, we are focusing on Placement and Routin For A Field Prorammable Multi-Chip Module Sanko Lan Avi Ziv Abbas El Gamal Information Systems Laboratory, Stanford University, Stanford, CA 94305 Abstract Placemen t and routin heuristics

More information

MOTION DETECTION BY CLASSIFICATION OF LOCAL STRUCTURES IN AIRBORNE THERMAL VIDEOS

MOTION DETECTION BY CLASSIFICATION OF LOCAL STRUCTURES IN AIRBORNE THERMAL VIDEOS In: Stilla U, Rottensteiner F, Hinz S (Eds) CMRT05. IAPRS, Vol. XXXVI, Part 3/W24 --- Vienna, Austria, Auust 29-30, 2005 MOTION DETECTION BY CLASSIFICATION OF LOCAL STRUCTURES IN AIRBORNE THERMAL VIDEOS

More information

x y x mod p g y mod p K= g xy mod p Alice Eve Bob g g x mod p x mod p g y y mod p y mod p K1= g mod p K2= g mod p

x y x mod p g y mod p K= g xy mod p Alice Eve Bob g g x mod p x mod p g y y mod p y mod p K1= g mod p K2= g mod p 6.857 Computer and Network Security Fall Term, 1997 Lecture 15 : October 23rd, 1997 Lecturer: Ron Rivest Scribe: Ben Adida 1 Topics Covered An Active Attack on RSA smart cards Secure Channels over Insecure

More information

Machining Feature Based Geometric Modeling of. Twist Drills

Machining Feature Based Geometric Modeling of. Twist Drills Machinin Feature Based Geometric Modelin of Twist Drills Jian Zhu A Thesis in The Department of Mechanical & Industrial Enineerin Presented in Partial Fulfillment of the Requirements for the Deree of Master

More information

THE FEASIBILITY OF SMOOTHED PARTICLE HYDRODYNAMICS FOR MULTIPHASE OILFIELD SYSTEMS

THE FEASIBILITY OF SMOOTHED PARTICLE HYDRODYNAMICS FOR MULTIPHASE OILFIELD SYSTEMS Seventh International Conference on CFD in the Minerals and Process Industries CSIRO, Melbourne, Australia 9-11 December 009 THE FEASIBILITY OF SMOOTHED PARTICLE HYDRODYNAMICS FOR MULTIPHASE OILFIELD SYSTEMS

More information

Heuristic Searching: A* Search

Heuristic Searching: A* Search IOSR Journal of Computer Enineerin (IOSRJCE) ISSN: 2278-0661 Volume 4, Issue 2 (Sep.-Oct. 2012), PP 01-05 Nazmul Hasan (Department of Computer Science and Enineerin, Military Institute of Science and Technoloy,

More information

Minimum-Cost Multicast Routing for Multi-Layered Multimedia Distribution

Minimum-Cost Multicast Routing for Multi-Layered Multimedia Distribution Minimum-Cost Multicast Routin for Multi-Layered Multimedia Distribution Hsu-Chen Chen and Frank Yeon-Sun Lin Department of Information Manaement, National Taiwan University 50, Lane 144, Keelun Rd., Sec.4,

More information

TETROBOT: A NOVEL MECHANISM FOR RECONFIGURABLE PARALLEL ROBOTICS. Student, Machine Building Faculty, Technical University of Cluj-Napoca

TETROBOT: A NOVEL MECHANISM FOR RECONFIGURABLE PARALLEL ROBOTICS. Student, Machine Building Faculty, Technical University of Cluj-Napoca UNIVERSITATEA TRANSILVANIA DIN BRA0OV Catedra Desin de Produs 1i Robotic2 Simpozionul na8ional cu participare interna8ional9 PRoiectarea ASIstat9 de Calculator P R A S I C ' 02 Vol. I Mecanisme 1i Triboloie

More information

Detecting Graph-Based Spatial Outliers: Algorithms and Applications(A Summary of Results) Λ y

Detecting Graph-Based Spatial Outliers: Algorithms and Applications(A Summary of Results) Λ y Detectin Graph-Based Spatial Outliers: Alorithms and Applications(A Summary of Results) Λ y Shashi Shekhar Department of Computer Science and Enineerin University of Minnesota 2 Union ST SE, 4-192 Minneapolis,

More information

Edgebreaker: Connectivity compression for triangle meshes

Edgebreaker: Connectivity compression for triangle meshes J. Rossinac GVU Technical Report GIT-GVU-98-35 (revised version of GIT-GVU-98-7) pae Edebreaker: Connectivity compression for trianle meshes Jarek Rossinac GVU Center, Georia Institute of Technoloy Abstract

More information

Adaptive multiple separation based on information maximization Kuang-Hung Liu and William H. Dragoset, WesternGeco

Adaptive multiple separation based on information maximization Kuang-Hung Liu and William H. Dragoset, WesternGeco Adaptive multiple separation based on information maximization Kuan-Hun Liu and William H. Draoset, WesternGeco Summary We are interested in the problem of separatin primary and multiple seismic sinals

More information

Framework. Fatma Ozcan Sena Nural Pinar Koksal Mehmet Altinel Asuman Dogac. Software Research and Development Center of TUBITAK

Framework. Fatma Ozcan Sena Nural Pinar Koksal Mehmet Altinel Asuman Dogac. Software Research and Development Center of TUBITAK Reion Based Query Optimizer Throuh Cascades Query Optimizer Framework Fatma Ozcan Sena Nural Pinar Koksal Mehmet ltinel suman Doac Software Research and Development Center of TUBITK Dept. of Computer Enineerin

More information

Sparsity-promoting migration from surface-related multiples Tim T.Y. Lin*, Ning Tu, and Felix J. Herrmann, University of British Columbia, EOS

Sparsity-promoting migration from surface-related multiples Tim T.Y. Lin*, Ning Tu, and Felix J. Herrmann, University of British Columbia, EOS Sparsity-promotin miration from surface-related multiples Tim T.Y. Lin*, Nin Tu, and Felix J. Herrmann, University of British Columbia, EOS SUMMARY Seismic imain typically beins with the removal of multiple

More information

Multi-scale Local Binary Pattern Histograms for Face Recognition

Multi-scale Local Binary Pattern Histograms for Face Recognition Multi-scale Local Binary Pattern Historams for Face Reconition Chi-Ho Chan, Josef Kittler, and Kieron Messer Centre for Vision, Speech and Sinal Processin, University of Surrey, United Kindom {c.chan,.kittler,k.messer}@surrey.ac.uk

More information

Survey On Image Texture Classification Techniques

Survey On Image Texture Classification Techniques Survey On Imae Texture Classification Techniques Vishal SThakare 1, itin Patil 2 and Jayshri S Sonawane 3 1 Department of Computer En, orth Maharashtra University, RCPIT Shirpur, Maharashtra, India 2 Department

More information

Numerical integration of discontinuous functions: moment fitting and smart octree

Numerical integration of discontinuous functions: moment fitting and smart octree Noname manuscript No. (will be inserted by the editor) Numerical interation of discontinuous functions: moment fittin and smart octree Simeon Hubrich Paolo Di Stolfo László Kudela Stefan Kollmannsberer

More information

The Gene Expression Messy Genetic Algorithm For. Hillol Kargupta & Kevin Buescher. Computational Science Methods division

The Gene Expression Messy Genetic Algorithm For. Hillol Kargupta & Kevin Buescher. Computational Science Methods division The Gene Expression Messy Genetic Alorithm For Financial Applications Hillol Karupta & Kevin Buescher Computational Science Methods division Los Alamos National Laboratory Los Alamos, NM, USA. Abstract

More information

Content Based Image Retrieval System with Regency Based Retrieved Image Library

Content Based Image Retrieval System with Regency Based Retrieved Image Library Content Based Imae Retrieval System with Reency Based Retrieved Imae Library Jadhav Seema H. #1,Dr.Sinh Sunita *2, Dr.Sinh Hari #3 #1 Associate Professor, Department of Instru & control, N.D.M.V.P.S s

More information

SBG SDG. An Accurate Error Control Mechanism for Simplification Before Generation Algorihms

SBG SDG. An Accurate Error Control Mechanism for Simplification Before Generation Algorihms An Accurate Error Control Mechanism for Simplification Before Generation Alorihms O. Guerra, J. D. Rodríuez-García, E. Roca, F. V. Fernández and A. Rodríuez-Vázquez Instituto de Microelectrónica de Sevilla,

More information

Imitation: An Alternative to Generalization in Programming by Demonstration Systems

Imitation: An Alternative to Generalization in Programming by Demonstration Systems Imitation: An Alternative to Generalization in Prorammin by Demonstration Systems Technical Report UW-CSE-98-08-06 Amir Michail University of Washinton amir@cs.washinton.edu http://www.cs.washinton.edu/homes/amir/opsis.html

More information

Fabric Defect Detection Based on Computer Vision

Fabric Defect Detection Based on Computer Vision Fabric Defect Detection Based on Computer Vision Jing Sun and Zhiyu Zhou College of Information and Electronics, Zhejiang Sci-Tech University, Hangzhou, China {jings531,zhouzhiyu1993}@163.com Abstract.

More information

Ch. 4 Physical Principles of CT

Ch. 4 Physical Principles of CT Ch. 4 Physical Principles of CT CLRS 408: Intro to CT Department of Radiation Sciences Review: Why CT? Solution for radiography/tomography limitations Superimposition of structures Distinguishing between

More information

1.2 Numerical Solutions of Flow Problems

1.2 Numerical Solutions of Flow Problems 1.2 Numerical Solutions of Flow Problems DIFFERENTIAL EQUATIONS OF MOTION FOR A SIMPLIFIED FLOW PROBLEM Continuity equation for incompressible flow: 0 Momentum (Navier-Stokes) equations for a Newtonian

More information

DESIGNER S NOTEBOOK Proximity Detection and Link Budget By Tom Dunn July 2011

DESIGNER S NOTEBOOK Proximity Detection and Link Budget By Tom Dunn July 2011 INTELLIGENT OPTO SENSOR Number 38 DESIGNER S NOTEBOOK Proximity Detection and Link Budget By Tom Dunn July 2011 Overview TAOS proximity sensors operate by flashing an infrared (IR) light towards a surface

More information

The SpecC Methodoloy Technical Report ICS December 29, 1999 Daniel D. Gajski Jianwen Zhu Rainer Doemer Andreas Gerstlauer Shuqin Zhao Department

The SpecC Methodoloy Technical Report ICS December 29, 1999 Daniel D. Gajski Jianwen Zhu Rainer Doemer Andreas Gerstlauer Shuqin Zhao Department The SpecC Methodoloy Technical Report ICS-99-56 December 29, 1999 Daniel D. Gajski Jianwen Zhu Rainer Doemer Andreas Gerstlauer Shuqin Zhao Department of Information and Computer Science University of

More information

Ecient and Precise Modeling of Exceptions for the Analysis of Java Programs. IBM Research. Thomas J. Watson Research Center

Ecient and Precise Modeling of Exceptions for the Analysis of Java Programs. IBM Research. Thomas J. Watson Research Center Ecient and Precise Modelin of Exceptions for the Analysis of Java Prorams Jon-Deok Choi David Grove Michael Hind Vivek Sarkar IBM Research Thomas J. Watson Research Center P.O. Box 704, Yorktown Heihts,

More information

Low cost concurrent error masking using approximate logic circuits

Low cost concurrent error masking using approximate logic circuits 1 Low cost concurrent error maskin usin approximate loic circuits Mihir R. Choudhury, Member, IEEE and Kartik Mohanram, Member, IEEE Abstract With technoloy scalin, loical errors arisin due to sinle-event

More information

Towards Plenoptic Dynamic Textures

Towards Plenoptic Dynamic Textures Towards Plenoptic Dynamic Textures Gianfranco Doretto UCLA Computer Science Department Los Aneles, CA 90095 Email: doretto@cs.ucla.edu Abstract We present a technique to infer a model of the spatio-temporal

More information

Compiler Optimization of Scalar Value Communication Between Speculative Threads

Compiler Optimization of Scalar Value Communication Between Speculative Threads Compiler Optimization of Scalar Value Communication Between Speculative Threads Antonia Zhai, Christopher B. Colohan, J. Greory Steffan, and Todd C. Mowry School of Computer Science Carneie Mellon University

More information

Summary. Introduction

Summary. Introduction Imae amplitude compensations: propaator amplitude recovery and acquisition aperture correction Jun Cao and Ru-Shan Wu Department of Earth and Planetary Sciences/IGPP, University of California, Santa Cruz

More information

Learning Geometric Concepts with an Evolutionary Algorithm. Andreas Birk. Universitat des Saarlandes, c/o Lehrstuhl Prof. W.J.

Learning Geometric Concepts with an Evolutionary Algorithm. Andreas Birk. Universitat des Saarlandes, c/o Lehrstuhl Prof. W.J. Learnin Geometric Concepts with an Evolutionary Alorithm Andreas Birk Universitat des Saarlandes, c/o Lehrstuhl Prof. W.J. Paul Postfach 151150, 66041 Saarbrucken, Germany cyrano@cs.uni-sb.de http://www-wjp.cs.uni-sb.de/cyrano/

More information

Effective Medium Theory, Rough Surfaces, and Moth s Eyes

Effective Medium Theory, Rough Surfaces, and Moth s Eyes Effective Medium Theory, Rough Surfaces, and Moth s Eyes R. Steven Turley, David Allred, Anthony Willey, Joseph Muhlestein, and Zephne Larsen Brigham Young University, Provo, Utah Abstract Optics in the

More information

TOWARD A UNIFIED INFORMATION SPACE FOR THE SPECIFICATION OF BUILDING PERFORMANCE SIMULATION RESULTS

TOWARD A UNIFIED INFORMATION SPACE FOR THE SPECIFICATION OF BUILDING PERFORMANCE SIMULATION RESULTS Ninth International IBPSA Conference Montréal, Canada Auust 15-18, 2005 TOWARD A UNIFIED INFORMATION SPACE FOR THE SPECIFICATION OF BUILDING PERFORMANCE SIMULATION RESULTS Ardeshir Mahdavi, Julia Bachiner,

More information

P2P network traffic control mechanism based on global evaluation values

P2P network traffic control mechanism based on global evaluation values June 2009, 16(3): 66 70 www.sciencedirect.com/science/ournal/10058885 The Journal of China Universities of Posts and Telecommunications www.buptournal.cn/ben P2P network traffic control mechanism based

More information

Morphological Image Processing

Morphological Image Processing Morphological Image Processing Binary image processing In binary images, we conventionally take background as black (0) and foreground objects as white (1 or 255) Morphology Figure 4.1 objects on a conveyor

More information

f y f x f z exu f xu syu s y s x s zl ezl f zl s zu ezu f zu sign logic significand multiplier exponent adder inc multiplexor multiplexor ty

f y f x f z exu f xu syu s y s x s zl ezl f zl s zu ezu f zu sign logic significand multiplier exponent adder inc multiplexor multiplexor ty A Combined Interval and Floatin Point Multiplier James E. Stine and Michael J. Schulte Computer Architecture and Arithmetic Laboratory Electrical Enineerin and Computer Science Department Lehih University

More information

IN SUPERSCALAR PROCESSORS DAVID CHU LIN. B.S., University of Illinois, 1990 THESIS. Submitted in partial fulllment of the requirements

IN SUPERSCALAR PROCESSORS DAVID CHU LIN. B.S., University of Illinois, 1990 THESIS. Submitted in partial fulllment of the requirements COMPILER SUPPORT FOR PREDICTED EXECUTION IN SUPERSCLR PROCESSORS BY DVID CHU LIN B.S., University of Illinois, 1990 THESIS Submitted in partial fulllment of the requirements for the deree of Master of

More information

Improving Hash Join Performance Through Prefetching

Improving Hash Join Performance Through Prefetching Improvin Hash Join Performance Throuh Prefetchin Shimin Chen, Anastassia Ailamaki, Phillip B. Gibbons, Todd C. Mowry Email: chensm@cs.cmu.edu, natassa@cs.cmu.edu, phillip.b.ibbons@intel.com, tcm@cs.cmu.edu

More information

in two important ways. First, because each processor processes lare disk-resident datasets, the volume of the communication durin the lobal reduction

in two important ways. First, because each processor processes lare disk-resident datasets, the volume of the communication durin the lobal reduction Compiler and Runtime Analysis for Ecient Communication in Data Intensive Applications Renato Ferreira Gaan Arawal y Joel Saltz Department of Computer Science University of Maryland, Collee Park MD 20742

More information

On Defending Peer-to-Peer System-based Active Worm Attacks

On Defending Peer-to-Peer System-based Active Worm Attacks This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE GLOBECOM 25 proceedins. On Defendin eer-to-eer System-based Active

More information

Using Excel for Graphical Analysis of Data

Using Excel for Graphical Analysis of Data Using Excel for Graphical Analysis of Data Introduction In several upcoming labs, a primary goal will be to determine the mathematical relationship between two variable physical parameters. Graphs are

More information

optimization agents user interface agents database agents program interface agents

optimization agents user interface agents database agents program interface agents A MULTIAGENT SIMULATION OPTIMIZATION SYSTEM Sven Hader Department of Computer Science Chemnitz University of Technoloy D-09107 Chemnitz, Germany E-Mail: sha@informatik.tu-chemnitz.de KEYWORDS simulation

More information

M3AR: A Privacy Preserving Algorithm that Maintains Association Rules

M3AR: A Privacy Preserving Algorithm that Maintains Association Rules M3A: A Privacy Preservin Alorithm that Maintains Association ules Huynh Van Quoc Phuon, ran Khanh Dan, Vo hi Noc Chau Faculty of Computer Science and Enineerin, HCMU National University of Ho Chi Minh

More information

Introduction to Digital Image Processing

Introduction to Digital Image Processing Fall 2005 Image Enhancement in the Spatial Domain: Histograms, Arithmetic/Logic Operators, Basics of Spatial Filtering, Smoothing Spatial Filters Tuesday, February 7 2006, Overview (1): Before We Begin

More information

CHAPTER 2 TEXTURE CLASSIFICATION METHODS GRAY LEVEL CO-OCCURRENCE MATRIX AND TEXTURE UNIT

CHAPTER 2 TEXTURE CLASSIFICATION METHODS GRAY LEVEL CO-OCCURRENCE MATRIX AND TEXTURE UNIT CHAPTER 2 TEXTURE CLASSIFICATION METHODS GRAY LEVEL CO-OCCURRENCE MATRIX AND TEXTURE UNIT 2.1 BRIEF OUTLINE The classification of digital imagery is to extract useful thematic information which is one

More information

Characterizing and Controlling the. Spectral Output of an HDR Display

Characterizing and Controlling the. Spectral Output of an HDR Display Characterizing and Controlling the Spectral Output of an HDR Display Ana Radonjić, Christopher G. Broussard, and David H. Brainard Department of Psychology, University of Pennsylvania, Philadelphia, PA

More information

Development of a variance prioritized multiresponse robust design framework for quality improvement

Development of a variance prioritized multiresponse robust design framework for quality improvement Development of a variance prioritized multiresponse robust desin framework for qualit improvement Jami Kovach Department of Information and Loistics Technolo, Universit of Houston, Houston, Texas 7704,

More information

DUAL energy X-ray radiography [1] can be used to separate

DUAL energy X-ray radiography [1] can be used to separate IEEE TRANSACTIONS ON NUCLEAR SCIENCE, VOL. 53, NO. 1, FEBRUARY 2006 133 A Scatter Correction Using Thickness Iteration in Dual-Energy Radiography S. K. Ahn, G. Cho, and H. Jeon Abstract In dual-energy

More information

Efficient Minimization of Sum and Differential Costs on Machines with Job Placement Constraints

Efficient Minimization of Sum and Differential Costs on Machines with Job Placement Constraints Efficient Minimization of Sum and Differential Costs on Machines with Job Placement Constraints Jaya Prakash Champati and Ben Lian Department of Electrical and Computer Enineerin, University of Toronto

More information

Optimal Scheduling of Dynamic Progressive Processing

Optimal Scheduling of Dynamic Progressive Processing Optimal Schedulin of Dynamic roressive rocessin Abdel-Illah ouaddib and Shlomo Zilberstein Abstract. roressive processin allows a system to satisfy a set of requests under time pressure by limitin the

More information

Energy-Conscious Co-Scheduling of Tasks and Packets in Wireless Real-Time Environments

Energy-Conscious Co-Scheduling of Tasks and Packets in Wireless Real-Time Environments Enery-Conscious Co-Schedulin of Tasks and Packets in Wireless Real- Environments Jun Yi, Christian Poellabauer, Xiaobo Sharon Hu, Jeff Simmer Department of Computer Science and Enineerin University of

More information

Automatic Inspection of Textured Surfaces by Support Vector Machines

Automatic Inspection of Textured Surfaces by Support Vector Machines Automatic Inspection of Textured Surfaces by Support Vector Machines Sina Jahanbin a, Alan C. Bovik a, Eduardo Pèrez b,dineshnair b a Department of Electrical and Computer Enineerin, the University of

More information

Software-based Compensation of Vibration-induced Errors of a Commercial Desktop 3D Printer

Software-based Compensation of Vibration-induced Errors of a Commercial Desktop 3D Printer 6th International Conference on Virtual Machinin Process Technoloy (VMPT), Montréal, May 29th June 2nd, 2017 Software-based Compensation of Vibration-induced Errors of a Commercial Desktop 3D Printer D.

More information

On the Network-Wide Gain of Memory-Assisted Source Coding

On the Network-Wide Gain of Memory-Assisted Source Coding 20 IEEE Information Theory Workshop On the etwork-wide Gain of Memory-Assisted Source Codin Mohsen Sardari, Ahmad Beirami, Faramarz Fekri School of Electrical and Computer Enineerin, Georia Institute of

More information

General Design of Grid-based Data Replication. Schemes Using Graphs and a Few Rules. availability of read and write operations they oer and

General Design of Grid-based Data Replication. Schemes Using Graphs and a Few Rules. availability of read and write operations they oer and General esin of Grid-based ata Replication Schemes Usin Graphs and a Few Rules Oliver Theel University of California epartment of Computer Science Riverside, C 92521-0304, US bstract Grid-based data replication

More information

Image Quality Assessment Techniques: An Overview

Image Quality Assessment Techniques: An Overview Image Quality Assessment Techniques: An Overview Shruti Sonawane A. M. Deshpande Department of E&TC Department of E&TC TSSM s BSCOER, Pune, TSSM s BSCOER, Pune, Pune University, Maharashtra, India Pune

More information

2. Background. Figure 1. Dependence graph used for scheduling

2. Background. Figure 1. Dependence graph used for scheduling Speculative Hede: Reulatin Compile-Time Speculation Aainst Prole Variations Brian L. Deitrich Wen-mei W. Hwu Center for Reliable and Hih-Performance Computin University of Illinois Urbana-Champain, IL

More information

Farming in the HERA-B Experiment

Farming in the HERA-B Experiment The HERA-B data acquisition and trierin systems make use of Linux farms for trierin and online event reconstruction. We present in this paper the requirements, implementation and performance of both farms.

More information

Analytical Modeling and Experimental Assessment of Five-Dimensional Capacitive Displacement Sensor

Analytical Modeling and Experimental Assessment of Five-Dimensional Capacitive Displacement Sensor Sensors and Materials, Vol. 29, No. 7 (2017) 905 913 MYU Tokyo 905 S & M 1380 Analytical Modelin and Experimental Assessment of Five-Dimensional Capacitive Displacement Sensor Jian-Pin Yu, * Wen Wan, 1

More information