Reconstruction of Orthogonal Polygonal Lines

Size: px
Start display at page:

Download "Reconstruction of Orthogonal Polygonal Lines"

Transcription

1 Recostructo of Orthogoal Polygoal Les Alexader Grbov ad Eugee Bodasky Evrometal System Research Isttute (ESRI) 380 New ork St. Redlads CA USA {agrbov Abstract. A orthogoal polygoal le s a le cosstg of adacet straght segmets havg oly two drectos orthogoal to each other. Because of ose ad vectorzato errors the result of vectorzato of such a le may dffer from a orthogoal polygoal le. Ths paper cotas the descrpto of a optmal method for the restorato of orthogoal polygoal les. It s based o the method of restorato of arbtrary groud truth les from the paper []. Specfcty of the algorthm suggested the paper cossts of flterg vectorzato errors usg a pror formato about orthogoalty of the groud truth cotour. The suggested algorthm guaratees that obtaed polygoal les wll be orthogoal ad have mmal devatos from the groud truth le. The algorthm has a low computatoal complexty ad ca be used for restorato of orthogoal polygoal les wth may vertces. It was developed for a rasterto-vector coverso system ArcSca for ArcGIS ad ca be used for teractve vectorzato of orthogoal polygoal les. Keywords: Polygoal le orthogoalty le drawgs maps vectorzato error flterg. Itroducto The term orthogoal polygoal les wll be used to refer to polygoal les cosstg of orthogoal straght segmets. There are oly two permssble drectos for these segmets. These are called cardal drectos. Ay two segmets of a orthogoal polygoal le are ether parallel or perpedcular to each other. Ay two successve segmets are perpedcular to each other. A rectagle s a example of a orthogoal polygoal le. Orthogoal polygoal les ca be see at dfferet le drawgs for example archtectural plas egeerg drawgs ad electrcal schematcs. Fg. shows a fragmet of a cty map. ost of the buldg outles are orthogoal les. The results of vectorzato of les from moochrome mages usually are corrupted. Because of scag ose dscretzato barzato ad vectorzato errors eve straght les are coverted to polygoal les after raw vectorzato. Fg. shows a moochrome mage obtaed by scag a straght le ad the result of raw vectorzato. The umber of segmets a resultg polygoal le ad the devatos of these segmets from the groud truth straght les are sometmes used to evaluate vectorzato error [].. Buke ad A.L. Sptz (Eds.): DAS 006 LNCS 387 pp Sprger-erlag Berl edelberg 006

2 Recostructo of Orthogoal Polygoal Les 463 Fg.. A fragmet of a cty map wth buldgs. ay of the buldg borders are orthogoal les. Fg.. The moochrome mage of straght les ad polygoal les as a result of raw vectorzato Post-processg usually follows raw vectorzato. Oe of the tasks of postprocessg s defragmetato. The goals of defragmetato are data compresso ad creasg precso. I the past data compresso was more mportat. The most wdely used compresso methods solve the problem of data compresso by removg some source polygoal le vertces (see for example the Douglas- Peucker method [3]). The ma crtero for removg a vertex s the dstace from the vertex of the source polygoal les to the polygoal le that s a result of compresso. Because the locato errors of the remag vertces are ot corrected the precso of vectorzato may ot be ehaced. I spte of ths the Douglas-Peucker compresso method s used tll ow for defragmetato ad smplfcato of polygoal les.

3 464 A. Grbov ad E. Bodasky Recetly because of cosderable reducto prce ad creasg capacty of computer memory the problem of data compresso has become less mportat whle the problem of ehacg the precso of vectorzato has become more crtcal. Oe approach to the problem of creasg vectorzato precso of polyles cosstg of geometrc prmtves follows. A source polygoal le obtaed by raw vectorzato s dvded to ooverlappg fragmets such that each could be approxmated wth good precso usg some geometrc prmtve (for example a straght segmet or a crcle arc). By fdg the optmal approxmatos of the prmtves ad the tersectos of adacet prmtves t s possble to buld a sequece of prmtves that s the restorato of groud truth le. The source polygoal le must be dvded such a way that some fuctoal that s a measure of approxmato error wll be mmzed. The vtal mportace of such a approach has a defto of the fuctoal. I [] such a approach s used wth oe restrcto (after dvdg the source le to fragmets they are approxmated oly wth straght segmets). The fuctoal value depeds ot oly o the precso of the approxmato of fragmets of source les but also o the umber of fragmets or the umber of straght segmets of the resultg polygoal le. Ths method uses oly oe parameter the pealty for each segmet of the resultg polygoal le. If the groud truth le s a orthogoal le the method suggested [] does ot guaratee that the resultg polygoal le wll be a orthogoal le. It s possble to resolve the problem by takg to accout geometrcal costrats ( ths case t s a orthogoalty) after a polygozato of the result of raw vectorzato (for example wth a beautfcato method from [4]). But the suggested method resolves the problem wth smultaeous polygozato ad takg to accout geometrc costrats. It provdes the capablty to dramatcally crease the accuracy of resultg polyles. A ew method of le fragmetato suggested ths paper dffers from the method descrbed [] by usg a pror formato that the groud truth le s a orthogoal le. Statemet of the Problem Let p where = 0... be vertces of polygoal le P. Let q -th vertces dvde P to a set of ooverlappg polygoal fragmets ad Q = { q0 = 0 q... qm = } be a set of dexes of the decomposto pots of a source polygoal le where m s a umber of segmets. Suppose that cardal drectos of the sought orthogoal polygoal le are horzotal ( ) ad vertcal ( ) drectos. Let X be oe of the cardal drectos ad X be a drecto perpedcular to X. Let L ad L be les havg cardal drectos X ad X ad mmal X X tegral stadard devatos ε X q q ad X ε q q from the correspodg p q

4 Recostructo of Orthogoal Polygoal Les 465 fragmet pq pq ) lmted wth q -th ad q -th vertces where ( =... of the source polygoal le (see Fg. 3). I Appedx there s a algorthm for buldg such les. m Fg. 3. Polygoal le P ad horzotal ad vertcal les ( L ad approxmatos of fragmets p q p ) ad q p ) = 0 ( 0 q L = p where 0 ( q The measure of the error of the orthogoal polygoal le approxmato s ( q q q q q q 0 m m ) are X X F Q X m) = m ( ε ε... ε ) () where s a pealty for each straght segmet of the resultg orthogoal polygoal le the secod tem s the sum of the tegral stadard devatos X s the drecto of the frst segmet ad s the drecto of the last segmet of the orthogoal polygoal le. X X Les L ad L are used for buldg orthogoal polygoal les. The vertces of the orthogoal polygoal les are the tersectos of adacet perpedcular les X X L ad L. The begg ad the ed of the orthogoal polygoal les are X proectos of pots p 0 ad p o les L ad L m. The task s to fd such set ˆ {ˆ ˆ... ˆ } Q = q q q ad values Xˆ ad ˆ that do 0 mˆ the value of the fuctoal () mmal. Ths set correspodg orthogoal polygoal le Qˆ drectos Xˆ ad ˆ ad Rˆ are optmal oes.

5 466 A. Grbov ad E. Bodasky 3 Iteratve Algorthm of Decomposto of a Polygoal Le to Fragmets Let k be a mmal error of approxmato of polygoal le P k wth orthogoal R k whe ad are fxed. The correspodg set of dces of P s Q k. The upper dex s a polygoal le decomposto pots of polygoal le k oretato of the last straght segmet of the orthogoal polygoal le. The mmum value of approxmato error of the polygoal le P k f the dex of the ext to last elemet s. The correspodg set ad orthogoal polygoal le k k are deoted Q k ad R. Obvously k = where = 0... k. Therefore k s the mmal value of ε k () for < k k 0. If the oretato of the frst segmet of the sought orthogoal polygoal le ukow ad so ca be horzotal or vertcal the 0 = = Rˆ s. (3) Suppose that all mmal errors of approxmato ad of polygoal le P k ad correspodg sets Q ad Q where =... k are kow. If mmum errors k ad k of P k ad correspodg set Qk ad Qk could be foud a teratve algorthm ca be buld to evaluate a optmal set Qˆ ad optmal orthogoal polygoal le Rˆ. Usg the method of least squares a horzotal or vertcal le ca be bult through the fragmet of the source polygoal le betwee vertces p ad p k ad the stadard devato ε k ad the mmal value of approxmato error k ca be calculated. By aalyzg k where = 0... k the mmum value of k ad correspodg value = ca be foud. Smlarly t ca be foud =. Sets Qk ad Q k ca be foud by addg k to sets Q ad Q respectvely (atteto must be pad to the sequece of superscrpts). Thus the problem s resolved.

6 Recostructo of Orthogoal Polygoal Les 467 Repeatg ths procedure tmes sets Q ad the mmum values of fuctoal () for gve values of ad. Q wll be obtaed that provde If the last segmet of the resultg orthogoal le must be horzotal or vertcal the the optmal sets are Q or Q respectvely. If there s o such requremet for the last segmet of the resultg orthogoal le the the optmal set s ˆ Q < ; = Q otherwse. Q (4) Fg. 4 shows the source polygoal le ad orthogoal le obtaed usg ths method. Fg. 4. Orthogoal polygoal le obtaed usg the descrbed method for = 30 (a - the source polygoal le b - orthogoal polygoal le c - the source ad the result le together) 4 Optmzato of the Iteratve Algorthm The algorthm descrbed above has the square calculatg complexty. It ca be used whe the source polygoal le does ot have may vertces for example a outle of buldgs maps of mddle scale. I the case whch the source le has may vertces the suggested algorthm ca cause a essetal delay. It s especally admssble for teractve modes. A techque to reduce the calculatg complexty of the descrbed algorthm s suggested. There are equaltes that ca be used for defg f a gve part of the polygoal le P k ca cota the ext to last pot of decomposto that mmzes k. Ths makes t uecessary to aalyze every vertex p where = 0... k of the polygoal le whle fdg a ew optmal pot. Ths techque s based o two obvous equaltes.

7 468 A. Grbov ad E. Bodasky The frst arses from the fact that a error of the optmal approxmato of a polygoal le wth two straght segmets s ot greater tha the error of the optmal approxmato of the same polygoal le wth oe straght segmet. ε where q q q X X X q ε q q ε q q q (5) 3 The secod equalty arses from the fact that the mmum error of the approxmato of some part of the polygoal le s ot greater tha the mmum error of the approxmato of the whole polygoal le. m{ q q } q (6) 0 q q ad s a drecto orthogoal to the drecto. where From equaltes (5) ad (6) t follows (see a Appedx ) that for q q < q k : 0 ~ q k q q k (7) ~ q k q k (8) where ~ { } q q k = m q q q k ε (9) P Deote ~ { } q k m q q q k ˆ = ε. (0) ~ ~ { q q k q k } q q k max =. () Suppose the value of the fuctoal of some decomposto of the polygoal le k where the ext to last pot of the decomposto does ot belog to the halfterval [ ) q was calculated. Deote ths fuctoal q q of decomposto for whch becomes mmal ca be located sde halfterval [ q q ) oly f q k F. The ext to last pot ˆ q q k F. () If ths codto s ot met the ext to last pot of decomposto does ot belog to [ q q ) ad ths half-terval ca be skpped. Usg ths t s possble to accelerate a search at each step of the descrbed teratve algorthm.

8 Recostructo of Orthogoal Polygoal Les Buldg a Close Orthogoal Polygoal Le The task of aalyzg a case whe the source polygoal le s closed as for example the borders of buldgs or other area obects ca be resolved by reducg t to the prevous oe. Frst t s ecessary to ope a source polygoal le other words to fd the begg. The frst pot ad the ed pot of the source le cocde p 0 = p. Let the frst pot be the upper-left vertex of the source le. Because of such choce of the begg of the polygoal le the error of approxmato s ot mmal but the addtoal error s small. Reorder the vertces so that a ew source polygoal le passes aroud the area obect a clockwse drecto. I ths case the frst segmet of the orthogoal polygoal le s horzotal. Therefore the last segmet must be vertcal because the le s closed. Whle the dervg the above algorthm to buld a orthogoal polygoal le t s assumed that the frst segmet of the orthogoal le ca be ether horzotal or vertcal. Substtutg 0 = 0 (3) stead of codto (3) the orthogoal polygoal le wth horzotal frst segmet X = s obtaed. Because the last segmet must be vertcal the codto Q ˆ = Q s used stead of codto (4). 0 = Fg. 5. A buldg ad approxmatos of ts border wth orthogoal polygoal les (a - raster mage of the buldg wth ose ad b-f - approxmatos of buldg borders obtaed wth accordgly) =

9 470 A. Grbov ad E. Bodasky Fg. 6. Image of three buldgs ad correspodg orthogoal polygoal les Fg. 5 shows a moochrome mage of a buldg (wth ose) ad orthogoal polygoal les obtaed wth dfferet values of. Fg. 6 shows a fragmet of a scaed map wth three buldgs ad orthogoal polygoal les obtaed wth the suggested method. 6 ow to Fd Cardal Drectos Usually cardal drectos are ot kow advace. Sometmes dfferet obects have dfferet cardal drectos (see for examples the borders of buldgs Fg. 6). I these cases the orthogoal polygoal les are bult N tmes wth oe of the cardal drectos α = h where h = 90 o / N ; = 0... N. (4) The coordate system s rotated to the agle α ad the task s resolved wth horzotal ad vertcal cardal drectos. The orthogoal polygoal le wth mmal error of approxmato s the desred soluto. The t s ecessary oly to tur t back through agle α. The value of N depeds o the requred precso. Usg dchotomy t s possble to crease the precso wth the same N. 7 Cocluso I ths paper the optmal method s suggested to recostruct orthogoal polygoal les after vectorzato. Ths method s based o the dyamc programmg techque. Because of errors caused by scag barzato vectorzato ad other processes eve straght les become polygoal les. Oe of the goals of postprocessg s ose flterg. I [] a ew method was suggested for flterg errors of vectorzato.

10 Recostructo of Orthogoal Polygoal Les 47 A polygoal le obtaed as a result of the raw vectorzato s dvded to o overlappg fragmets. The method guaratees the mmum value of the fuctoal that depeds o precso of approxmato of resultg parts wth straght segmets ad o the umber of parts or the umber of segmets of the result polygoal le. Ths method uses oe parameter a pealty for each straght segmet of the resultg polygoal le. The error of approxmato s calculated as tegral stadard error. It s possble to modfy the method usg aother measure of the error. By fdg tersectos of straght les obtaed as a optmal approxmato of fragmets a ew polygoal le ca be bult. Fg. 7. A fragmet of the cty map from Fg. wth borders of orthogoal buldgs (the result of processg by ArcSca for ArcGIS) The method descrbed ths paper s a modfcato of the method from []. odfyg ts method wth a pror formato that the sought polygoal le s a orthogoal le provdes the method descrbed ths paper. Ths method guaratees that the resultg polygoal le wll be a orthogoal le wth almost mmal error compared to the source orthogoal polygoal le. The method s a combatoral oe ad has the quadratc computato complexty. There was a suggested optmzato that reduces the umber of aalyzed solutos whch essetally creases the speed of resolvg the task. After optmzato the algorthm ca be used for recostructo of the orthogoal polygoal les from the source polygoal les wth a large umber of vertces whch s commo for polygoal les obtaed wth vectorzato. The method has bee geeralzed for closed orthogoal polygoal les for example borders of buldgs maps. The polygoal le must have segmets roughly equal sze to a pxel; otherwse t s ecessary to perform desfcato.

11 47 A. Grbov ad E. Bodasky The method ca also be geeralzed for the followg cases: Decomposto of the source polygoal les to fragmets some of whch are sgular (wth zero legth) Polygoal les wth a fxed agle betwee adacet segmets dfferg from 90 Polygoal les wth the arbtrary umber of permssble drectos -dmesoal polygoal les where > 0 The method has bee mplemeted ArcSca for ArcGIS. Examples Fg. 4-7 show the results obtaed wth the suggested method. Refereces. Grbov A. Bodasky E.: A New ethod of Polyle Approxmato. Structural Sytactc ad Statstcal Patter Recogto Portugal LNCS 338 Sprger (August 004) Phllps I.T. Chhabra A.K.: Emprcal Performace Evaluato of Graphcs Recogto Systems. IEEE Trasactos o Patter Aalyss ad ache Itellgece ol. No. 9 (September 999) Davd. Douglas ad Thomas K. Peucker: Algorthms for the Reducto of the Number of Pots Requred to Represet a Dgtzed Le or Its Carcature. Caada Cartographer ol. 0 No. (December 973) - 4. Pavlds T. awyk C.J.: A Automatc Beautfer for Drawgs ad Illustratos. Computer Graphcs ol. 9 No. 3 AC Press (July 985) 5-34 Appedx : orzotal ad ertcal Les Approxmatg Some Part of the Polygoal Le Let t be a parameter equal to the dstace from the begg of the polygoal le tll the curret pot alog ths le. Let l ad l be values of the parameter defg the begg ad the ed of the aalyzed part of the polygoal le. The horzotal le approxmatg a gve part of the polygoal le ca be defed as The vertcal le ca be foud smlarly y x l y = where y = () l l y t l dt. l x = where x = () l l x t l dt.

12 Recostructo of Orthogoal Polygoal Les 473 Itegral stadard devatos of these straght les are defed as l = y y l () t dt ( l l ) ε l = x x l () t dt ( l l ) ε. Appedx : Dervato of Iequaltes (7) ad (8) 0 Let q q < q k. From equaltes () ad (6) ad obvous equalty possble to obta { } q k q q q k expresso (9). From equaltes () ad (5) follows ε q k q k ε t s m ε other words q k q q q q k ε. ε q q q m q q From a obvous equalty { } follows q k m { q q } q k ε t ε or expresso (0).

For all questions, answer choice E) NOTA" means none of the above answers is correct. A) 50,500 B) 500,000 C) 500,500 D) 1,001,000 E) NOTA

For all questions, answer choice E) NOTA means none of the above answers is correct. A) 50,500 B) 500,000 C) 500,500 D) 1,001,000 E) NOTA For all questos, aswer choce " meas oe of the above aswers s correct.. What s the sum of the frst 000 postve tegers? A) 50,500 B) 500,000 C) 500,500 D),00,000. What s the sum of the tegers betwee 00 ad

More information

Eight Solved and Eight Open Problems in Elementary Geometry

Eight Solved and Eight Open Problems in Elementary Geometry Eght Solved ad Eght Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew eght prevous proposed ad solved problems of elemetary

More information

Nine Solved and Nine Open Problems in Elementary Geometry

Nine Solved and Nine Open Problems in Elementary Geometry Ne Solved ad Ne Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew e prevous proposed ad solved problems of elemetary D geometry

More information

Office Hours. COS 341 Discrete Math. Office Hours. Homework 8. Currently, my office hours are on Friday, from 2:30 to 3:30.

Office Hours. COS 341 Discrete Math. Office Hours. Homework 8. Currently, my office hours are on Friday, from 2:30 to 3:30. Oce Hours Curretly, my oce hours are o Frday, rom :30 to 3:30. COS 31 Dscrete Math 1 Oce Hours Curretly, my oce hours are o Frday, rom :30 to 3:30. Nobody seems to care. Chage oce hours? Tuesday, 8 PM

More information

Eight Solved and Eight Open Problems in Elementary Geometry

Eight Solved and Eight Open Problems in Elementary Geometry Eght Solved ad Eght Ope Problems Elemetary Geometry Floret Smaradache Math & Scece Departmet Uversty of New Mexco, Gallup, US I ths paper we revew eght prevous proposed ad solved problems of elemetary

More information

Bezier curves. 1. Defining a Bezier curve. A closed Bezier curve can simply be generated by closing its characteristic polygon

Bezier curves. 1. Defining a Bezier curve. A closed Bezier curve can simply be generated by closing its characteristic polygon Curve represetato Copyrght@, YZU Optmal Desg Laboratory. All rghts reserved. Last updated: Yeh-Lag Hsu (--). Note: Ths s the course materal for ME55 Geometrc modelg ad computer graphcs, Yua Ze Uversty.

More information

Face Recognition using Supervised & Unsupervised Techniques

Face Recognition using Supervised & Unsupervised Techniques Natoal Uversty of Sgapore EE5907-Patter recogto-2 NAIONAL UNIVERSIY OF SINGAPORE EE5907 Patter Recogto Project Part-2 Face Recogto usg Supervsed & Usupervsed echques SUBMIED BY: SUDEN NAME: harapa Reddy

More information

Region Matching by Optimal Fuzzy Dissimilarity

Region Matching by Optimal Fuzzy Dissimilarity Rego Matchg by Optmal Fuzzy Dssmlarty Zhaggu Zeg, Ala Fu ad Hog Ya School of Electrcal ad formato Egeerg The Uversty of Sydey Phoe: +6--935-6659 Fax: +6--935-3847 Emal: zzeg@ee.usyd.edu.au Abstract: Ths

More information

Clustering documents with vector space model using n-grams

Clustering documents with vector space model using n-grams Clusterg documets wth vector space model usg -grams Klas Skogmar, d97ksk@efd.lth.se Joha Olsso, d97jo@efd.lth.se Lud Isttute of Techology Supervsed by: Perre Nugues, Perre.Nugues@cs.lth.se Abstract Ths

More information

Fitting. We ve learned how to detect edges, corners, blobs. Now what? We would like to form a. compact representation of

Fitting. We ve learned how to detect edges, corners, blobs. Now what? We would like to form a. compact representation of Fttg Fttg We ve leared how to detect edges, corers, blobs. Now what? We would lke to form a hgher-level, h l more compact represetato of the features the mage b groupg multple features accordg to a smple

More information

Transistor/Gate Sizing Optimization

Transistor/Gate Sizing Optimization Trasstor/Gate Szg Optmzato Gve: Logc etwork wth or wthout cell lbrary Fd: Optmal sze for each trasstor/gate to mmze area or power, both uder delay costrat Statc szg: based o tmg aalyss ad cosder all paths

More information

Vanishing Point Detection: Representation Analysis and New Approaches

Vanishing Point Detection: Representation Analysis and New Approaches Publshed the Proceedgs of the th Iteratoal Coferece o Image Aalyss ad Processg (ICIAP ). IEEE. Persoal use of ths materal s permtted. However, permsso to reprt/republsh ths materal for advertsg or promotoal

More information

Descriptive Statistics: Measures of Center

Descriptive Statistics: Measures of Center Secto 2.3 Descrptve Statstcs: Measures of Ceter Frequec dstrbutos are helpful provdg formato about categorcal data, but wth umercal data we ma wat more formato. Statstc: s a umercal measure calculated

More information

Chapter 3 Descriptive Statistics Numerical Summaries

Chapter 3 Descriptive Statistics Numerical Summaries Secto 3.1 Chapter 3 Descrptve Statstcs umercal Summares Measures of Cetral Tedecy 1. Mea (Also called the Arthmetc Mea) The mea of a data set s the sum of the observatos dvded by the umber of observatos.

More information

COMPARISON OF PARAMETERIZATION METHODS USED FOR B-SPLINE CURVE INTERPOLATION

COMPARISON OF PARAMETERIZATION METHODS USED FOR B-SPLINE CURVE INTERPOLATION Europea Joural of Techc COMPARISON OF PARAMETERIZATION METHODS USED FOR B-SPLINE CURVE INTERPOLATION Sıtı ÖZTÜRK, Cegz BALTA, Melh KUNCAN 2* Kocael Üverstes, Mühedsl Faültes, Eletro ve Haberleşme Mühedslğ

More information

International Mathematical Forum, 1, 2006, no. 31, ON JONES POLYNOMIALS OF GRAPHS OF TORUS KNOTS K (2, q ) Tamer UGUR, Abdullah KOPUZLU

International Mathematical Forum, 1, 2006, no. 31, ON JONES POLYNOMIALS OF GRAPHS OF TORUS KNOTS K (2, q ) Tamer UGUR, Abdullah KOPUZLU Iteratoal Mathematcal Forum,, 6, o., 57-54 ON JONES POLYNOMIALS OF RAPHS OF TORUS KNOTS K (, q ) Tamer UUR, Abdullah KOPUZLU Atatürk Uverst Scece Facult Dept. of. Math. 54 Erzurum, Turkey tugur@atau.edu.tr

More information

NUMERICAL INTEGRATION BY GENETIC ALGORITHMS. Vladimir Morozenko, Irina Pleshkova

NUMERICAL INTEGRATION BY GENETIC ALGORITHMS. Vladimir Morozenko, Irina Pleshkova 5 Iteratoal Joural Iformato Theores ad Applcatos, Vol., Number 3, 3 NUMERICAL INTEGRATION BY GENETIC ALGORITHMS Vladmr Morozeko, Ira Pleshkova Abstract: It s show that geetc algorthms ca be used successfully

More information

Probabilistic properties of topologies of finite metric spaces minimal fillings.

Probabilistic properties of topologies of finite metric spaces minimal fillings. arxv:308.656v [math.mg] Aug 03 Probablstc propertes of topologes of fte metrc spaces mmal fllgs. Vsevolod Salkov Abstract I ths work we provde a way to troduce a probablty measure o the space of mmal fllgs

More information

Machine Learning: Algorithms and Applications

Machine Learning: Algorithms and Applications /03/ Mache Learg: Algorthms ad Applcatos Florao Z Free Uversty of Boze-Bolzao Faculty of Computer Scece Academc Year 0-0 Lecture 3: th March 0 Naïve Bayes classfer ( Problem defto A trag set X, where each

More information

Searching the Optimal Threshold for Voxel Coloring in 3D Reconstruction

Searching the Optimal Threshold for Voxel Coloring in 3D Reconstruction Searchg the Optmal Threshold or oxel Colorg D Recostructo Youg-Youl Y, Hyo-Sug Km, Soo-Youg Ye, K-Go Nam Departmet o Electroc Egeerg, Pusa Natoal Uversty Emal: mustapha@pusa.ac.r Abstract oxel colorg s

More information

COMSC 2613 Summer 2000

COMSC 2613 Summer 2000 Programmg II Fal Exam COMSC 63 Summer Istructos: Name:. Prt your ame the space provded Studet Id:. Prt your studet detfer the space Secto: provded. Date: 3. Prt the secto umber of the secto whch you are

More information

1-D matrix method. U 4 transmitted. incident U 2. reflected U 1 U 5 U 3 L 2 L 3 L 4. EE 439 matrix method 1

1-D matrix method. U 4 transmitted. incident U 2. reflected U 1 U 5 U 3 L 2 L 3 L 4. EE 439 matrix method 1 -D matrx method We ca expad the smple plae-wave scatterg for -D examples that we ve see to a more versatle matrx approach that ca be used to hadle may terestg -D problems. The basc dea s that we ca break

More information

Self-intersection Avoidance for 3-D Triangular Mesh Model

Self-intersection Avoidance for 3-D Triangular Mesh Model Self-tersecto Avodace for 3-D Tragular Mesh Model Habtamu Masse Aycheh 1) ad M Ho Kyug ) 1) Departmet of Computer Egeerg, Ajou Uversty, Korea, ) Departmet of Dgtal Meda, Ajou Uversty, Korea, 1) hab01@ajou.ac.kr

More information

A Genetic K-means Clustering Algorithm Applied to Gene Expression Data

A Genetic K-means Clustering Algorithm Applied to Gene Expression Data A Geetc K-meas Clusterg Algorthm Appled to Gee Expresso Data Fag-Xag Wu, W. J. Zhag, ad Athoy J. Kusal Dvso of Bomedcal Egeerg, Uversty of Sasatchewa, Sasatoo, S S7N 5A9, CANADA faw34@mal.usas.ca, zhagc@egr.usas.ca

More information

PERSPECTIVES OF THE USE OF GENETIC ALGORITHMS IN CRYPTANALYSIS

PERSPECTIVES OF THE USE OF GENETIC ALGORITHMS IN CRYPTANALYSIS PERSPECTIVES OF THE USE OF GENETIC ALGORITHMS IN CRYPTANALYSIS Lal Besela Sokhum State Uversty, Poltkovskaa str., Tbls, Georga Abstract Moder cryptosystems aalyss s a complex task, the soluto of whch s

More information

MINIMIZATION OF THE VALUE OF DAVIES-BOULDIN INDEX

MINIMIZATION OF THE VALUE OF DAVIES-BOULDIN INDEX MIIMIZATIO OF THE VALUE OF DAVIES-BOULDI IDEX ISMO ÄRÄIE ad PASI FRÄTI Departmet of Computer Scece, Uversty of Joesuu Box, FI-800 Joesuu, FILAD ABSTRACT We study the clusterg problem whe usg Daves-Bould

More information

Blind Steganalysis for Digital Images using Support Vector Machine Method

Blind Steganalysis for Digital Images using Support Vector Machine Method 06 Iteratoal Symposum o Electrocs ad Smart Devces (ISESD) November 9-30, 06 Bld Stegaalyss for Dgtal Images usg Support Vector Mache Method Marcelus Hery Meor School of Electrcal Egeerg ad Iformatcs Badug

More information

LP: example of formulations

LP: example of formulations LP: eample of formulatos Three classcal decso problems OR: Trasportato problem Product-m problem Producto plag problem Operatos Research Massmo Paolucc DIBRIS Uversty of Geova Trasportato problem The decso

More information

Prof. Feng Liu. Winter /24/2019

Prof. Feng Liu. Winter /24/2019 Prof. Feg Lu Wter 209 http://www.cs.pd.edu/~flu/courses/cs40/ 0/24/209 Last Tme Feature detecto 2 Toda Feature matchg Fttg The followg sldes are largel from Prof. S. Lazebk 3 Wh etract features? Motvato:

More information

A PROCEDURE FOR SOLVING INTEGER BILEVEL LINEAR PROGRAMMING PROBLEMS

A PROCEDURE FOR SOLVING INTEGER BILEVEL LINEAR PROGRAMMING PROBLEMS ISSN: 39-8753 Iteratoal Joural of Iovatve Research Scece, Egeerg ad Techology A ISO 397: 7 Certfed Orgazato) Vol. 3, Issue, Jauary 4 A PROCEDURE FOR SOLVING INTEGER BILEVEL LINEAR PROGRAMMING PROBLEMS

More information

A Comparison of Heuristics for Scheduling Spatial Clusters to Reduce I/O Cost in Spatial Join Processing

A Comparison of Heuristics for Scheduling Spatial Clusters to Reduce I/O Cost in Spatial Join Processing Edth Cowa Uversty Research Ole ECU Publcatos Pre. 20 2006 A Comparso of Heurstcs for Schedulg Spatal Clusters to Reduce I/O Cost Spatal Jo Processg Jta Xao Edth Cowa Uversty 0.09/ICMLC.2006.258779 Ths

More information

Using The ACO Algorithm in Image Segmentation for Optimal Thresholding 陳香伶財務金融系

Using The ACO Algorithm in Image Segmentation for Optimal Thresholding 陳香伶財務金融系 教專研 95P- Usg The ACO Algorthm Image Segmetato for Optmal Thresholdg Abstract Usg The ACO Algorthm Image Segmetato for Optmal Thresholdg 陳香伶財務金融系 Despte the fact that the problem of thresholdg has bee qute

More information

An Enhanced Local Covering Approach for Minimization of Multiple-Valued Input Binary-Valued Output Functions

An Enhanced Local Covering Approach for Minimization of Multiple-Valued Input Binary-Valued Output Functions Proceedgs of the 10th WSEAS Iteratoal Coferece o COMPUTERS, Voulagme, Athes, Greece, July 13-15, 2006 (pp63-68) A Ehaced Local Coverg Approach for Mmzato of Multple-Valued Iput Bary-Valued Output Fuctos

More information

Area and Power Efficient Modulo 2^n+1 Multiplier

Area and Power Efficient Modulo 2^n+1 Multiplier Iteratoal Joural of Moder Egeerg Research (IJMER) www.jmer.com Vol.3, Issue.3, May-Jue. 013 pp-137-1376 ISSN: 49-6645 Area ad Power Effcet Modulo ^+1 Multpler K. Ptambar Patra, 1 Saket Shrvastava, Sehlata

More information

An Optimal Thresholding Method for the Voxel Coloring in the 3D Shape Reconstruction

An Optimal Thresholding Method for the Voxel Coloring in the 3D Shape Reconstruction ICCAS00 Jue -, KINTEX, Gyeogg-Do, Korea A Optmal Thresholdg Method or the oxel Colorg the D Shape Recostructo Soo-Youg Ye*, Hyo-Sug Km*, Youg-Youl Y*, ad K-Go Nam ** * Dept. o Electrocs Egr., Pusa Natoal

More information

ChEn 475 Statistical Analysis of Regression Lesson 1. The Need for Statistical Analysis of Regression

ChEn 475 Statistical Analysis of Regression Lesson 1. The Need for Statistical Analysis of Regression Statstcal-Regresso_hadout.xmcd Statstcal Aalss of Regresso ChE 475 Statstcal Aalss of Regresso Lesso. The Need for Statstcal Aalss of Regresso What do ou do wth dvdual expermetal data pots? How are the

More information

On a Sufficient and Necessary Condition for Graph Coloring

On a Sufficient and Necessary Condition for Graph Coloring Ope Joural of Dscrete Matheatcs, 04, 4, -5 Publshed Ole Jauary 04 (http://wwwscrporg/joural/ojd) http://dxdoorg/0436/ojd04400 O a Suffcet ad Necessary Codto for raph Colorg Maodog Ye Departet of Matheatcs,

More information

Parallel Iterative Poisson Solver for a Distributed Memory Architecture

Parallel Iterative Poisson Solver for a Distributed Memory Architecture Parallel Iteratve Posso Solver for a Dstrbted Memory Archtectre Erc Dow Aerospace Comptatoal Desg Lab Departmet of Aeroatcs ad Astroatcs 2 Motvato Solvg Posso s Eqato s a commo sbproblem may mercal schemes

More information

CS 2710 Foundations of AI Lecture 22. Machine learning. Machine Learning

CS 2710 Foundations of AI Lecture 22. Machine learning. Machine Learning CS 7 Foudatos of AI Lecture Mache learg Mlos Hauskrecht mlos@cs.ptt.edu 539 Seott Square Mache Learg The feld of mache learg studes the desg of computer programs (agets) capable of learg from past eperece

More information

Laplacian Meshes Deformation Based on the Offset of Sketching

Laplacian Meshes Deformation Based on the Offset of Sketching JOURNAL OF SOFTWARE, VOL. 7, NO. 9, SEPTEMBER 202 2083 Laplaca Meshes Deformato Based o the Offset of Sketchg Sha Chemg School of Software, Harb Uversty of Scece ad Techology, Harb, Cha Emal: shachm@63.com

More information

Workflow- Based Shape Optimization of Airfoils and Blades using Chained Bezier Curves

Workflow- Based Shape Optimization of Airfoils and Blades using Chained Bezier Curves Workflow- Based Shape Optmzato of Arfols ad Blades usg Chaed Bezer Curves Igor Pehec, Damr Vuča, Želja Loza Faculty of Electrcal Egeerg, Mechacal Egeerg ad Naval Archtecture FESB, Uversty of Splt, Croata

More information

Vertex Odd Divisor Cordial Labeling of Graphs

Vertex Odd Divisor Cordial Labeling of Graphs IJISET - Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue 0, October 0. www.jset.com Vertex Odd Dvsor Cordal Labelg of Graphs ISSN 48 68 A. Muthaya ad P. Pugaleth Assstat Professor, P.G.

More information

SVM Classification Method Based Marginal Points of Representative Sample Sets

SVM Classification Method Based Marginal Points of Representative Sample Sets P P College P P College P Iteratoal Joural of Iformato Techology Vol. No. 9 005 SVM Classfcato Method Based Margal Pots of Represetatve Sample Sets Wecag ZhaoP P, Guagrog JP P, Ru NaP P, ad Che FegP of

More information

Beijing University of Technology, Beijing , China; Beijing University of Technology, Beijing , China;

Beijing University of Technology, Beijing , China; Beijing University of Technology, Beijing , China; d Iteratoal Coferece o Machery, Materals Egeerg, Chemcal Egeerg ad Botechology (MMECEB 5) Research of error detecto ad compesato of CNC mache tools based o laser terferometer Yuemg Zhag, a, Xuxu Chu, b

More information

Mode-based temporal filtering for in-band wavelet video coding with spatial scalability

Mode-based temporal filtering for in-band wavelet video coding with spatial scalability Mode-based temporal flterg for -bad wavelet vdeo codg wth spatal scalablty ogdog Zhag a*, Jzheg Xu b, Feg Wu b, Weju Zhag a, ogka Xog a a Image Commucato Isttute, Shagha Jao Tog Uversty, Shagha b Mcrosoft

More information

A Traffic Camera Calibration Method Based on Multi-rectangle

A Traffic Camera Calibration Method Based on Multi-rectangle Traffc Camera Calbrato Method ased o Mult-rectagle Lyg Lu Xaobo Lu Sapg J Che Tog To cte ths verso: Lyg Lu Xaobo Lu Sapg J Che Tog. Traffc Camera Calbrato Method ased o Multrectagle. Zhogzh Sh; Zhaohu

More information

Optimal Allocation of Complex Equipment System Maintainability

Optimal Allocation of Complex Equipment System Maintainability Optmal Allocato of Complex Equpmet System ataablty X Re Graduate School, Natoal Defese Uversty, Bejg, 100091, Cha edcal Protecto Laboratory, Naval edcal Research Isttute, Shagha, 200433, Cha Emal:rexs841013@163.com

More information

APR 1965 Aggregation Methodology

APR 1965 Aggregation Methodology Sa Joaqu Valley Ar Polluto Cotrol Dstrct APR 1965 Aggregato Methodology Approved By: Sged Date: March 3, 2016 Araud Marjollet, Drector of Permt Servces Backgroud Health rsk modelg ad the collecto of emssos

More information

Mesh Connectivity Compression for Progressive-to-Lossless Transmission

Mesh Connectivity Compression for Progressive-to-Lossless Transmission Mesh Coectvty Compresso for Progressve-to-Lossless Trasmsso Pegwe Hao, Yaup Paer ad Ala Pearma ISSN 1470-5559 RR-05-05 Jue 005 Departmet of Computer Scece Mesh Coectvty Compresso for Progressve-to-Lossless

More information

A New Approach for Reconstructed B-spline Surface Approximating to Scattered Data Points. Xian-guo CHENG

A New Approach for Reconstructed B-spline Surface Approximating to Scattered Data Points. Xian-guo CHENG 2016 Iteratoal Coferece o Computer, Mechatrocs ad Electroc Egeerg (CMEE 2016 ISBN: 978-1-60595-406-6 A New Approach for Recostructed B-sple Surface Approxmatg to Scattered Data Pots Xa-guo CHENG Ngbo Uversty

More information

A New Newton s Method with Diagonal Jacobian Approximation for Systems of Nonlinear Equations

A New Newton s Method with Diagonal Jacobian Approximation for Systems of Nonlinear Equations Joural of Mathematcs ad Statstcs 6 (3): 46-5, ISSN 549-3644 Scece Publcatos A New Newto s Method wth Dagoal Jacoba Appromato for Systems of Nolear Equatos M.Y. Wazr, W.J. Leog, M.A. Hassa ad M. Mos Departmet

More information

Denoising Algorithm Using Adaptive Block Based Singular Value Decomposition Filtering

Denoising Algorithm Using Adaptive Block Based Singular Value Decomposition Filtering Advaces Computer Scece Deosg Algorthm Usg Adaptve Block Based Sgular Value Decomposto Flterg SOMKAIT UDOMHUNSAKUL Departmet of Egeerg ad Archtecture Rajamagala Uversty of Techology Suvarabhum 7/ Suaya,

More information

Speeding- Up Fractal Image Compression Using Entropy Technique

Speeding- Up Fractal Image Compression Using Entropy Technique Avalable Ole at www.jcsmc.com Iteratoal Joural of Computer Scece ad Moble Computg A Mothly Joural of Computer Scece ad Iformato Techology ISSN 2320 088X IMPACT FACTOR: 5.258 IJCSMC, Vol. 5, Issue. 4, Aprl

More information

QUADRATURE POINTS ON POLYHEDRAL ELEMENTS

QUADRATURE POINTS ON POLYHEDRAL ELEMENTS QUADRATURE POINTS ON POLYHEDRAL ELEMENTS Tobas Pck, Peter Mlbradt 2 ABSTRACT The method of the fte elemets s a flexble umerc procedure both for terpolato ad approxmato of the solutos of partal dfferetal

More information

Theoretical Computer Science

Theoretical Computer Science Theoretcal Computer Scece 40 009 949 957 Cotets lsts avalable at SceceDrect Theoretcal Computer Scece joural homepage: www.elsever.com/locate/tcs Improved approxmato bouds for edge domatg set dese graphs

More information

ECE Digital Image Processing and Introduction to Computer Vision

ECE Digital Image Processing and Introduction to Computer Vision ECE59064 Dgtal Image Processg ad Itroducto to Computer Vso Depart. of ECE NC State Uverst Istructor: Tafu Matt Wu Sprg 07 Outle Recap Le Segmet Detecto Fttg Least square Total square Robust estmator Hough

More information

Announcements. Fitting: Announcements. Some seam carving results 9/24/2009. Thursday, Sept 24 Kristen Grauman UT-Austin

Announcements. Fitting: Announcements. Some seam carving results 9/24/2009. Thursday, Sept 24 Kristen Grauman UT-Austin 9/4/9 Aoucemets Fttg: Deformable cotours Thursday, Sept 4 Krste Grauma UT-Aust Next week : guest lectures Tuesday : Backgroud modelg Thursday : Image formato Yog Jae ad I are ot avalable for offce hours

More information

NEURO FUZZY MODELING OF CONTROL SYSTEMS

NEURO FUZZY MODELING OF CONTROL SYSTEMS NEURO FUZZY MODELING OF CONTROL SYSTEMS Efré Gorrosteta, Carlos Pedraza Cetro de Igeería y Desarrollo Idustral CIDESI, Av Pe de La Cuesta 70. Des. Sa Pablo. Querétaro, Qro, Méxco gorrosteta@teso.mx pedraza@cdes.mx

More information

ITEM ToolKit Technical Support Notes

ITEM ToolKit Technical Support Notes ITEM ToolKt Notes Fault Tree Mathematcs Revew, Ic. 2875 Mchelle Drve Sute 300 Irve, CA 92606 Phoe: +1.240.297.4442 Fax: +1.240.297.4429 http://www.itemsoft.com Page 1 of 15 6/1/2016 Copyrght, Ic., All

More information

MOTION RECOVERY BASED ON FEATURE EXTRACTION FROM 2D IMAGES

MOTION RECOVERY BASED ON FEATURE EXTRACTION FROM 2D IMAGES MOTION RECOVERY BASED ON FEATURE EXTRACTION FROM 2D IMAGES Jahu Zhao, Lg L 2 ad Kwoh Chee Keog 3,3 School of Computer Egeerg, Nayag Techologcal Uversty, Sgapore, 639798 2 School of Computg, Curt Uversty

More information

Constructive Semi-Supervised Classification Algorithm and Its Implement in Data Mining

Constructive Semi-Supervised Classification Algorithm and Its Implement in Data Mining Costructve Sem-Supervsed Classfcato Algorthm ad Its Implemet Data Mg Arvd Sgh Chadel, Arua Twar, ad Naredra S. Chaudhar Departmet of Computer Egg. Shr GS Ist of Tech.& Sc. SGSITS, 3, Par Road, Idore (M.P.)

More information

CC-MODELER: A TOPOLOGY GENERATOR FOR 3-D CITY MODELS

CC-MODELER: A TOPOLOGY GENERATOR FOR 3-D CITY MODELS D. Frtsch, M. Eglch & M. Sester, eds, 'IAPRS', Vol. 32/4, ISPRS Commsso IV Symposum o GIS - Betwee Vsos ad Applcatos, Stuttgart, Germay. CC-MODELER: A TOPOLOGY GENERATOR FOR 3-D CITY MODELS Arm Grue Xhua

More information

CLUSTERING ASSISTED FUNDAMENTAL MATRIX ESTIMATION

CLUSTERING ASSISTED FUNDAMENTAL MATRIX ESTIMATION CLUSERING ASSISED FUNDAMENAL MARIX ESIMAION Hao Wu ad Y Wa School of Iformato Scece ad Egeerg, Lazhou Uversty, Cha wuhao1195@163com, wayjs@163com ABSRAC I computer vso, the estmato of the fudametal matrx

More information

BODY MEASUREMENT USING 3D HANDHELD SCANNER

BODY MEASUREMENT USING 3D HANDHELD SCANNER Movemet, Health & Exercse, 7(1), 179-187, 2018 BODY MEASUREMENT USING 3D HANDHELD SCANNER Mohamed Najb b Salleh *, Halm b Mad Lazm, ad Hedrk b Lamsal Techology ad Supply Cha Isttute, School of Techology

More information

Fingerprint Classification Based on Spectral Features

Fingerprint Classification Based on Spectral Features Fgerprt Classfcato Based o Spectral Features Hosse Pourghassem Tarbat Modares Uversty h_poorghasem@modares.ac.r Hassa Ghassema Tarbat Modares Uversty ghassem@modares.ac.r Abstract: Fgerprt s oe of the

More information

Short Vector SIMD Code Generation for DSP Algorithms

Short Vector SIMD Code Generation for DSP Algorithms Short Vector SMD Code Geerato for DSP Algorthms Fraz Frachett Chrstoph Ueberhuber Appled ad Numercal Mathematcs Techcal Uversty of Vea Austra Markus Püschel José Moura Electrcal ad Computer Egeerg Carege

More information

Clustered Signatures for Modeling and Recognizing 3D Rigid Objects

Clustered Signatures for Modeling and Recognizing 3D Rigid Objects World Academy of Scece, Egeerg ad Techology 4 008 Clustered Sgatures for Modelg ad Recogzg 3D Rgd Obects H. B. Darbad, M. R. Ito, ad J. Lttle Abstract Ths paper descrbes a probablstc method for three-dmesoal

More information

DEEP (Displacement Estimation Error Back-Propagation) Method for Cascaded ViSPs (Visually Servoed Paired Structured Light Systems)

DEEP (Displacement Estimation Error Back-Propagation) Method for Cascaded ViSPs (Visually Servoed Paired Structured Light Systems) DEEP (Dsplacemet Estmato Error Back-Propagato) Method for Cascaded VSPs (Vsually Servoed Pared Structured Lght Systems) Haem Jeo 1), Jae-Uk Sh 2), Wachoel Myeog 3), Yougja Km 4), ad *Hyu Myug 5) 1), 3),

More information

Comparison Studies on Classification for Remote Sensing Image Based on Data Mining Method

Comparison Studies on Classification for Remote Sensing Image Based on Data Mining Method Hag Xao ad Xub Zhag Comparso Studes o Classfcato for Remote Sesg Image Based o Data Mg Method Hag XIAO 1, Xub ZHANG 1 1: School of Electroc, Iformato ad Electrcal Egeerg Shagha Jaotog Uversty No. 1954,

More information

Electrocardiogram Classification Method Based on SVM

Electrocardiogram Classification Method Based on SVM Electrocardogram Classfcato Method Based o SVM Xao Tag Zhwe Mo College of mathematcs ad software scece, Schua ormal uversty, Chegdu 60066, P. R. Cha Abstract Heart dsease s oe of the ma dseases threateg

More information

Point Estimation-III: General Methods for Obtaining Estimators

Point Estimation-III: General Methods for Obtaining Estimators Pot Estmato-III: Geeral Methods for Obtag Estmators RECAP 0.-0.6 Data: Radom Sample from a Populato of terest o Real valued measuremets: o Assumpto (Hopefully Reasoable) o Model: Specfed Probablty Dstrbuto

More information

Signal-Path Driven Partition and Placement for Analog Circuit

Signal-Path Driven Partition and Placement for Analog Circuit Sgal-Path Drve Partto ad Placemet for Aalog Crcut D Log Xalog Hog Sheq Dog EDA Lab Departmet of Computer Scece ad Techology Tsghua Uversty Beg 100084 Cha logd02@malstsghuaeduc; hxl-dcs@maltsghuaeduc; dogsq@maltsghuaeduc

More information

Spatial Error Concealment Based on Bezier Curves Ocultamiento de Errores Espacial Mediante Curvas de Bezier

Spatial Error Concealment Based on Bezier Curves Ocultamiento de Errores Espacial Mediante Curvas de Bezier Computacó y Sstemas Vol. 9 Núm. 3, pp. 256-269 2006, CIC-IPN, ISSN 1405-5546, Impreso e Méxco Ocultameto de Errores Espacal Medate Curvas de Bezer Rogelo Hasmoto-Beltrá 1 ad Ashfaq A. Khokhar 2 1 Cetro

More information

Greater Knowledge Extraction Based on Fuzzy Logic And GKPFCM Clustering Algorithm

Greater Knowledge Extraction Based on Fuzzy Logic And GKPFCM Clustering Algorithm 6th WSEAS It. Coferece o Computatoal Itellgece, Ma-Mache Systems ad Cyberetcs, Teerfe, Spa, December 14-16, 2007 47 Greater Kowledge Extracto Based o uzzy Logc Ad GKPCM Clusterg Algorthm BEJAMÍ OJEDA-MAGAÑA

More information

Search and Surveillance in emergency situations A GIS-based approach to construct optimal visibility graphs

Search and Surveillance in emergency situations A GIS-based approach to construct optimal visibility graphs Mor et al. Costructg optmal vsblty graphs Search ad Survellace emergecy stuatos A GIS-based approach to costruct optmal vsblty graphs Mchael Mor, Irèe Ab-Zed, 2, Thah Tug Nguye, Luc Lamotage Departmet

More information

A Comparison of Univariate Smoothing Models: Application to Heart Rate Data Marcus Beal, Member, IEEE

A Comparison of Univariate Smoothing Models: Application to Heart Rate Data Marcus Beal, Member, IEEE A Comparso of Uvarate Smoothg Models: Applcato to Heart Rate Data Marcus Beal, Member, IEEE E-mal: bealm@pdx.edu Abstract There are a umber of uvarate smoothg models that ca be appled to a varety of olear

More information

Constructing Scalable 3D Animated Model by Deformation Sensitive Simplification

Constructing Scalable 3D Animated Model by Deformation Sensitive Simplification Costructg Scalable 3D Amated Model by Deformato Seste Smplfcato Sheg-Yao Cho Natoal Tawa Uersty e@cmlab.cse.tu.edu.tw Bg-Yu Che Natoal Tawa Uersty rob@tu.edu.tw ABSTRACT To date, more hgh resoluto amated

More information

A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases

A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases A Smple Dmesoalty Reducto Techque for Fast Smlarty Search Large Tme Seres Databases Eamo J. Keogh ad Mchael J. Pazza Departmet of Iformato ad Computer Scece Uversty of Calfora, Irve, Calfora 92697 USA

More information

AT MOST EDGE 3 - SUM CORDIAL LABELING FOR SOME GRAPHS THE STANDARD

AT MOST EDGE 3 - SUM CORDIAL LABELING FOR SOME GRAPHS THE STANDARD Iteratoal Joural o Research Egeerg ad Appled Sceces IJREAS) Avalable ole at http://euroasapub.org/ourals.php Vol. x Issue x, July 6, pp. 86~96 ISSNO): 49-395, ISSNP) : 349-655 Impact Factor: 6.573 Thomso

More information

A Novel Optimization Algorithm for Adaptive Simplex Method with Application to High Dimensional Functions

A Novel Optimization Algorithm for Adaptive Simplex Method with Application to High Dimensional Functions A Novel Optmzato Algorthm for Adaptve Smplex Method th Applcato to Hgh Dmesoal Fuctos ZuoYg LIU, XaWe LUO 2 Southest Uversty Chogqg 402460, Cha, zuyglu@alyu.com 2 Southest Uversty Chogqg 402460, Cha, xael@su.edu.c.

More information

Some Results on Vertex Equitable Labeling

Some Results on Vertex Equitable Labeling Ope Joural of Dscrete Mathematcs, 0,, 5-57 http://dxdoorg/0436/odm0009 Publshed Ole Aprl 0 (http://wwwscrporg/oural/odm) Some Results o Vertex Equtable Labelg P Jeyath, A Maheswar Research Cetre, Departmet

More information

SALAM A. ISMAEEL Computer Man College for Computer Studies, Khartoum / Sudan

SALAM A. ISMAEEL Computer Man College for Computer Studies, Khartoum / Sudan AAPTIVE HYBRI-WAVELET ETHO FOR GPS/ SYSTE INTEGRATION SALA A. ISAEEL Computer a College for Computer Studes, Khartoum / Suda salam.smaeel@gmal.com ABSTRACT I ths paper, a techque for estmato a global postog

More information

VOLUME MESHING USING A COUPLED DELAUNAY TRIANGULATION WITH ADVANCING FRONT TECHNIQUE MATHEMATICAL FOUNDATION

VOLUME MESHING USING A COUPLED DELAUNAY TRIANGULATION WITH ADVANCING FRONT TECHNIQUE MATHEMATICAL FOUNDATION JAN KUCWAJ VOLUME MESHING USING A COUPLED DELAUNAY TRIANGULATION WITH ADVANCING FRONT TECHNIQUE MATHEMATICAL FOUNDATION TRIANGULACJA OBSZARÓW PRZESTRZENNYCH METODĄ POSTĘPUJĄCEGO FRONTU POŁĄCZONĄ Z TRIANGULACJĄ

More information

Automated approach for the surface profile measurement of moving objects based on PSP

Automated approach for the surface profile measurement of moving objects based on PSP Uversty of Wollogog Research Ole Faculty of Egeerg ad Iformato Sceces - Papers: Part B Faculty of Egeerg ad Iformato Sceces 207 Automated approach for the surface profle measuremet of movg objects based

More information

Texture-Based Segmentation of 3D Probabilistic Occupancy Maps for Robot Navigation

Texture-Based Segmentation of 3D Probabilistic Occupancy Maps for Robot Navigation Abstract Texture-Based Segmetato of 3D Probablstc Occupacy Maps for Robot Navgato Bassel Abou Merhy, Perre Payeur, Eml M. Petru School of Iformato Techology ad Egeerg Uversty of Ottawa, Ottawa, ON, Caada

More information

An Improved Fuzzy C-Means Clustering Algorithm Based on Potential Field

An Improved Fuzzy C-Means Clustering Algorithm Based on Potential Field 07 d Iteratoal Coferece o Advaces Maagemet Egeerg ad Iformato Techology (AMEIT 07) ISBN: 978--60595-457-8 A Improved Fuzzy C-Meas Clusterg Algorthm Based o Potetal Feld Yua-hag HAO, Zhu-chao YU *, X GAO

More information

A Feature Based Method of Image Matching for computing stereo models

A Feature Based Method of Image Matching for computing stereo models > REPLCE THIS LINE WITH YOUR PPER IDENTIFICTION NUMER (DOULE-CLICK HERE TO EDIT) < Feature ased Method of Image Matchg for computg stereo models Ch-Kou Shu bstract The purpose of ths paper s to propose

More information

3D Polygon Rendering Pipeline

3D Polygon Rendering Pipeline 2008 סמסטר ב' ליאור שפירא קורס גרפיקה ממוחשבת 3D Rederg Ppele (for drect llumato) 3D Polygo Rederg Ppele Sca Coverso & Shadg Thomas Fukhouser Prceto Uversty C0S 426, Fall 1999 3D Prmtves 3D Modelg Coordates

More information

Estimating Feasibility Using Multiple Surrogates and ROC Curves

Estimating Feasibility Using Multiple Surrogates and ROC Curves Estmatg Feasblty Usg Multple Surrogates ad ROC Curves Arba Chaudhur * Uversty of Florda, Gaesvlle, Florda, 3601 Rodolphe Le Rche École Natoale Supéreure des Mes de Sat-Étee, Sat-Étee, Frace ad CNRS LIMOS

More information

AN IMPROVED TEXT CLASSIFICATION METHOD BASED ON GINI INDEX

AN IMPROVED TEXT CLASSIFICATION METHOD BASED ON GINI INDEX Joural of Theoretcal ad Appled Iformato Techology 30 th September 0. Vol. 43 No. 005-0 JATIT & LLS. All rghts reserved. ISSN: 99-8645 www.jatt.org E-ISSN: 87-395 AN IMPROVED TEXT CLASSIFICATION METHOD

More information

Delay based Duplicate Transmission Avoid (DDA) Coordination Scheme for Opportunistic routing

Delay based Duplicate Transmission Avoid (DDA) Coordination Scheme for Opportunistic routing Delay based Duplcate Trasmsso Avod (DDA) Coordato Scheme for Opportustc routg Ng L, Studet Member IEEE, Jose-Fera Martez-Ortega, Vcete Heradez Daz Abstract-Sce the packet s trasmtted to a set of relayg

More information

Airline Fleet Routing and Flight Scheduling under Market Competitions. Tang and Ming-Chei

Airline Fleet Routing and Flight Scheduling under Market Competitions. Tang and Ming-Chei Arle Fleet Routg ad Flght Schedulg uder Market Compettos Shagyao Ya, Ch-Hu Tag ad Mg-Che Lee Departmet of Cvl Egeerg, Natoal Cetral Uversty 3/12/2009 Itroducto Lterature revew The model Soluto method Numercal

More information

REVISTA INVESTIGACION OPERACIONAL Vol. 23, No. 1, 2002

REVISTA INVESTIGACION OPERACIONAL Vol. 23, No. 1, 2002 REVISTA INVESTIGACION OERACIONAL Vol. 3, No., FITTING A CONIC A-SLINE TO CONTOUR IMAGE DATA V. Herádez Mederos, D. Martíez Morera y J. Estrada Sarlabous 3 Isttuto de Cberétca, Matemátca y Físca, ICIMAF,

More information

New Fuzzy Integral for the Unit Maneuver in RTS Game

New Fuzzy Integral for the Unit Maneuver in RTS Game New Fuzzy Itegral for the Ut Maeuver RTS Game Peter Hu Fug Ng, YgJe L, ad Smo Ch Keug Shu Departmet of Computg, The Hog Kog Polytechc Uversty, Hog Kog {cshfg,csyjl,csckshu}@comp.polyu.edu.hk Abstract.

More information

Image Analysis. Segmentation by Fitting a Model. Christophoros Nikou We ve learned how to detect edges, corners, blobs. Now what?

Image Analysis. Segmentation by Fitting a Model. Christophoros Nikou We ve learned how to detect edges, corners, blobs. Now what? Image Aalyss Fttg Segmetato y Fttg a Model Chrstophoros Nkou ckou@cs.uo.gr Images take from: D. Forsyth ad J. Poce. Computer Vso: A Moder Approach, Pretce Hall, 003. Computer Vso course y Svetlaa Lazek,

More information

GUI Simulation Platform for RFID Indoor Tracking System

GUI Simulation Platform for RFID Indoor Tracking System Sesors & Trasducers 2014 by IFSA Publshg, S. L. http://www.sesorsportal.com GUI Smulato Platform for RFID Idoor Trackg System 1 Be-Be Mao, 2 JIN Xue-Bo School of Computer ad Iformato Egeerg, Bejg Techology

More information

Research on Circular Target Center Detection Algorithm Based on Morphological Algorithm and Subpixel Method

Research on Circular Target Center Detection Algorithm Based on Morphological Algorithm and Subpixel Method Research o Crcular Target Ceter Detecto Algorthm Based o Morphologcal Algorthm ad Subpxel Method Yu Le 1, Ma HuZhu 1, ad Yag Wezhou 1 1 College of Iformato ad Commucato Egeerg, Harb Egeerg Uversty, Harb

More information

EDGE- ODD Gracefulness of the Tripartite Graph

EDGE- ODD Gracefulness of the Tripartite Graph EDGE- ODD Graceuless o the Trpartte Graph C. Vmala, A. Saskala, K. Ruba 3, Asso. Pro, Departmet o Mathematcs, Peryar Maamma Uversty, Vallam, Thajavur Post.. Taml Nadu, Ida. 3 M. Phl Scholar, Departmet

More information

Evaluation of Node and Link Importance Based on Network Topology and Traffic Information DU Xun-Wei, LIU Jun, GUO Wei

Evaluation of Node and Link Importance Based on Network Topology and Traffic Information DU Xun-Wei, LIU Jun, GUO Wei Advaced Materals Research Submtted: 2014-08-29 ISSN: 1662-8985, Vols. 1049-1050, pp 1765-1770 Accepted: 2014-09-01 do:10.4028/www.scetfc.et/amr.1049-1050.1765 Ole: 2014-10-10 2014 Tras Tech Publcatos,

More information

Effects of Exterior Orientation Elements on Direct Georeferencing in POS-Supported Aerial Photogrammetry

Effects of Exterior Orientation Elements on Direct Georeferencing in POS-Supported Aerial Photogrammetry Proceedgs of the 8th Iteratoal mposum o patal Accurac Assessmet atural Resources ad Evrometal ceces hagha P. R. Cha Jue 5-7 008 pp. 30-36 Effects of Eteror Oretato Elemets o Drect Georeferecg PO-upported

More information