CALIBRATION OF A STRUCTURED LIGHT-BASED STEREO CATADIOPTRIC SENSOR *

Size: px
Start display at page:

Download "CALIBRATION OF A STRUCTURED LIGHT-BASED STEREO CATADIOPTRIC SENSOR *"

Transcription

1 AIBRATION OF A STRUTURED IGHT-BASED STEREO ATADIOPTRI SENSOR * Rdu Orghidn, Joquim Slvi, El Mustph Mouddi omputer Vision nd Rootics Group, Institute of Informtics nd Applictions, Universitt de Giron, Avd. luis Sntlo, s/n Giron, tloni (Spin) entre de Rootique, Electrotechnique et d Automtique, Université de Picrdie Jules Verne, Rue du Moulin Neuf 8 Amiens, Frnce ABSTRAT tdioptric sensors re comintions of mirrors nd lenses mde in order to otin ide field of vie. In this pper e propose ne sensor tht hs omnidirectionl vieing ility nd it lso provides depth informtion out the nery surrounding. The sensor is sed on conventionl cmer coupled ith lser emitter nd to hyperolic mirrors. Mthemticl formultion nd precise specifictions of the intrinsic nd etrinsic prmeters of the sensor re discussed. Our pproch overcomes limittions of the eisting omnidirectionl sensors nd eventully leds to reduced costs of production. Keyords: omnidirectionl vie, hyperolic mirror, lser, structured light, stereo vision 1. INTRODUTION A lrge field of vie is n ttrctive gol in computer vision. Potentil pplictions re in the domins of surveillnce, teleconferencing, unknon environment eplortion, tourism, dvertising etc. Moreover, egomotion estimtion nd oject trcking cn lrgely enefit from enhncing the field of vie of imging systems. The idel omnidirectionl device is system hving the cpility to see simultneously 36º in ll directions. In this y pnormic imge of the environment is continuously processed. There re mny proposls for uilding omnidirectionl sensors: ) specil lenses such s fish-eye lenses; ) multiple imge cquisition y mens of rotting cmers or using structures of mny cmers ith complementry fields of vie; nd c) cmers ith especil mirrors (plnr, hyperolic, prolic, sphericl, dul conve nd conic) [3]. * A common constrint upon the omnidirectionl sensors modelling requires tht ll the imged rys pss through n unique point clled single vie-point (SVP). This is n importnt feture ecuse it permits the distortion-free * Work funded y the Spnish project IYT TAP reconstruction of the imge. onsequently, the omnidirectionl sensors cn e clssified depending on hether they hve SVP or not. Nyr nd Bker [4] eplored the clss of SVP ctdioptric sensors tht produce SVP. Omnidirectionl vie cn e chieved y mens of fisheye lenses ith the disdvntge tht such lenses introduce rdil distortion tht complictes the mthemticl model. The otined imges hve good resolution on the centrl region ut hve poor resolution on the mrginl region. Furthermore, fish-eye lenses do not meet the SVP constrint. High resolution pnormic vies cn e otined using multiple imges provided y rotting cmer. The min drck of this method is tht the pnormic imge is not formed ith single cpture. Moreover, omnidirectionl vie is formed from severl prtil imges, hich cn led to discontinuities in the resulting imge if the cmer is not precisely controlled involving loer roustness nd constrining the use of these sensors in root pplictions. mers ith complementry fields of vie overcome some prolems of the previous method ecuse there re not moving prts ut the sensor ecomes more epensive nd difficult to clirte since it involves severl cmers. The comintions of mirrors (ctoptrics) nd lenses (dioptrics) is clled ctdioptrics. A 36º horiontl field of vie is chieved t every cpture using single cmer looking into conve mirror. For instnce, Pegrd nd Mouddi [] uilt such sensor ith conic mirror hile Ym et l. [4] used hyperolic mirror. Both otined good results for root nvigtion nd loclition. Stereo ctdioptric sensors re specil structures of ctdioptrics used to otin depth from to omnidirectionl imges. Nene nd Nyr [1] studied severl stereo configurtions using the mirrors hich hve SVP. Also, Gluckmn et l. [9] designed ctdioptric stereo sensor sed on to prolic mirrors ith to cmers. Southell et l. [7] studied the ide of tringultion y mens of ctdioptric sensor ith iloed mirror. ter, Ollis [6] simulted vrious configurtions using to hyperolic mirrors ith one nd

2 to cmers. Depth mesurements ere otined y tringultion. The correspondence prolem s solved y indo mtching eteen oth imges y mens of correltion lgorithm considering the curvture of the mirrors. Fil nd Bsu [5] uilt such sensor using emedded sphericl mirror loes. Depth mesurements ere lso otined y mens of feture etrction nd tringultion. Besides, structured light is technique idely used to mesure 3D surfces y the projection of sequence of light ptterns [11]. The mesuring surfce is emphsised y the pprent deformtions of the imged pttern from the projected one. Such light ptterns re projected y mens of slide projectors, digitl projectors or lser light emitters hich forms different shpe of ptterns. Slides re difficult to use ith clirted systems ecuse of the deformtions cused y the functioning temperture of the projector lmp. Besides, digitl projectors hve focusing prolems hich limits the depth rnge of the mesuring re. Finlly, lser light offers ttrctive fetures such s monochromtic light hich permits the use of opticl filters for stright-forrd imge segmenttion. ser projectors re thin nd cn e plced inside compct devices. The eperiments conducted y Bldin nd Bsu [8] demonstrte tht right lights improves mtching, therefore, lser light seems good choice. Hoever, lser emitters cn only project simple types of ptterns such s points, lines nd grids. This pper presents ne ctdioptric pnormic sensor ith n emedded structured light projector. In section, severl possile configurtions re compred nd the mtemticl model of the most desirle one is nlyed. Section 3 dels ith the design of the optiml sie of the mirrors. The clirtion method is descried in section 4. Then, section 5 presents the simulted results of the proposed sensor. The rticle ends ith conclusions.. SENSOR DESIGN tdioptric devices cn e clssified relted to the SVP constrint. For instnce, sphericl shped mirrors do not meet such constrint nd the lck of perspective point mkes more complicted the imge reconstruction process. Nevertheless, sphericl mirrors re preferred for mnufcturility resons nd for specific properties such s the compct sie or the equl chrcteristics over imuth [5][7][8]. The second ctegory contins the mirrors tht meet the SVP constrint: the prol, the ellipse nd the hyperol. The prolic mirror orks in the sme y s the prolic ntenn. The incoming rys pss through the focl point nd re then reflected prllel to the rotting is of the prol. Therefore, in order to use the SVP property, the imge must e formed y cmer ith orthogrphic lenses. This is n epensive type of cmer nd increses the price of the ctdioptric device. Besides, the ellipsoid mirror hs smll prcticl use since the reflecting prt nd the cmer must e on the inner side of the surfce providing n ineffective field of vie. Finlly, the hyperolic mirror cn e oserved using common perspective cmer, therefore is considered n ttrctive choice. In ddition, stereo omnidirectionl using structured light cn e reched y mens of comintions of to hyperolic mirrors, cmer nd lser projector (figure 1). The mirrors re symmetricl out the is so the idimensionl grphicl representtion is lloed. The first configurtion (fig. 1.) is sed on to identicl mirrors locted long seline hich cn e fied depending on the ccurcy desired. The light pttern is projected onto.. c. d. e. Figure 1. Stereo omnidirectionl systems (the dotted lines ound the cmer nd the lser self-occlusion regions). one of the mirrors hile the other mirror grs the scene. The mirrors re clled lser mirror nd cmer mirror, respectively. Such setting, mkes invlule prt of the imge ecuse of the scene occlusion cused y the lser projector. This prolem cn e solved y plcing oth mirrors ck to ck long the rottion is (see fig 1.). Such system removes the occlusion prolem ut the lser hs to e projected on the peripherl sie of the mirror (in order to e seen y the cmer mirror) here mjor lens distortion is present leding to poorer resolution of the system. Plcing the to mirrors y single trnsltion long the verticl is (see fig 1.c), permits the lser to e projected nery the centre of the mirror here etter resolution is given ut the deth re of the cmer mirror is sted leding to lrger system. A nturl solution is to put the lser mirror inside the deth cone given y the cmer mirror (Fig 1.d) otining compct sensor, yet, ith the inconvenient tht the lser mirror occludes prt of the vision field of the cmer mirror. In order to void this prolem nd to enhnce the seline, the to mirrors cn e seprted (Fig 1.e). Tking into ccount the previous oservtions, ne ctdioptric sensor is proposed (see fig.). The sensor is composed of to hyperolic mirrors, lser projector nd cmer. The cmer nd the lser emitter re oth represented using the pinhole model since the

3 projector cn e seen s n inverted cmer. The lser emits circle onto the lser mirror hich is projected forrd 36º ll round the mesuring scene nd ckrds to the cmer mirror into the imge plne. Depth informtion is retrieved y nlying the D projection on the cmer of the points of the scene enlightened y the lser pttern. These points re isolted y n opticl filter nd further imge segmenttion techniques. The cmer mirror complies ith the SVP criteri, therefore the line on hich lys n oject point P cn e determined from its projective imge point Pi. The lser mirror enefits of the sme properties, tht is: the line long hich point of the pttern is projected cn lso e defined. Depth informtion is otined y crossing oth lines. Herefter, complete description of the sensor is detiled. Figure. Stereo ctdioptric sensor ith structured light projector. The ngle of vie (α) of the sensor is the ngle eteen F, P1 nd F,, here F (,y, ) is the focl point of the cmer mirror, P1 is the highest reflecting point of the mirror nd is the projection of point Pm on the cmer mirror. The ngle α nd the rnge of vie (Rov) determine the position of the highest (PM) nd loest (Pm) points of scene imged y the sensor. These points re reflected on the lser mirror on points P1 nd P, respectively. The focl points of the lser mirror (F) nd the cmer mirror (F) re ligned long the rottion is nd trnslted distnce dff. The hyperolic shpes of the cmer nd the lser mirrors re modeled y equtions (1) nd (), respectively. (( dff) + + ) + y 1 Solving eqution (1) for to solutions re found, hich re the equtions of the upper (3) nd loer (4) hyperols. e + + y + (3) 1 e + y + (4) here, e +. The prmeters of ech mirror re supposed to e linked y k/, here k is constnt vlue. The focl point of the cmer (F cmer ) is plced in the focus of the loer hyperol, t distnce dfe from F. The light em emitted y n infinitely smll point of the pttern hits the lser mirror in point (P) tht cn e clculted y solving the system formed y equtions () nd the eqution of the line defined y the light em. According to the SVP constrint, P is projected long the line F, P t n oject point PW hich is projected onto the cmer mirror t (, y, ), otining eqution (5) nd (6). PW(,y, ) is determined y tringultion since it elongs to oth lines F, P nd F,. ( + + ) y y y y + y () 1 (5) There re to solutions of the system ut only the point closer to the emitting light source must e considered. The coordintes of s function of PW re given y eqution (7). y 1, 1, 1, y P e (6) ( e + P ) (7) 1, 1, here, P + y +. Besides, the points F, P nd P re on the sme line. Since the coordintes of the points F,, F nd P re knon, the point PW is uniquely determined. ( + + ) + y 1 (1) 3. DESIGN OF THE OPTIMA MIRROR SIZE An importnt concern hen designing the sensor is its sie. The sensor is designed to e used in indoor

4 environments so it hs to e smll. Besides, imge processing requires good resolution hich is improved y using lrge mirrors. A compromise must e set up in order to otin optiml performnces. Figure 3. The reltion eteen R top, the sie of the sensor nd the intrinsic prmeters of the cmer In figure 3, P y is the imge point of the cmer mirror rim on the D, d is the distnce from the centre of the D to P y, f is the focl distnce of the cmer nd h is the verticl distnce from the focl point of the mirror to its order. Idelly, the cmer mirror is imged y the cmer s disc tngent to the D order, therefore, severl constrints hve to e tken into ccount during the design process of the sensor: onstrint 1. The point P1 must e on the line F, PM (fig 1.) so tht the cmer mirror is le to see the highest points of the required field of vie. onstrint. The points of the cmer mirror rim must e close to the line P y, P1 for n optimlly sied imge in the cmer. onstrint 3. From severl suitle hyperolic shpes for the cmer mirror the one ith the igger deth re is chosen since it ill provide lrger cone for plcing the structured light projector. A numeric lgorithm produces ll hyperolic shpes ithin given rnge for specific vlues of α, R top nd Rov. Every shpe is compred ith the idel one nd the shpes ith n error elo threshold re kept. According to third constrint, the desired one is selected. The reltion eteen r d nd FF is shon in figure 3. Vlues for severl shpes hve een clculted nd re presented in Tle 1. The most suitle one depends on the finl ppliction of the system. Figure 4. Vlues of r d nd dff for mirror shpes ith the prmeter vrying from up to 15. Tle 1. The prmeters for suitle sensors α R top H r top df AIBRATION In the folloing, the clirtion of the sensor is done in to steps considering first the clirtion of the pir cmer nd cmer mirror (see section 3.1) hich is then used for the clirtion of the pir lser nd lser mirror (see section 3.) The pir cmer nd cmer mirror. The pir formed y the cmer nd its coupled mirror is modelled y eqution (8). D M W Pi K K M F( KW P) (8) here: W P is knon oject point respect to the orld coordinte system, P i is the imge point corresponding to the projection of W P, M K W is the trnsformtion mtri tht reltes the orld coordinte system ith respect to the mirror coordinte system, K M is the trnsformtion mtri tht reltes the mirror coordinte system ith respect to the cmer coordinte system, D K is the projection mtri tht models the internl geometry of the cmer y set of intrinsic prmeters: α u u (9) D K α v v 1 here: α u f ku, α v f kv So, the projection of n oject point W P onto the mirror (otining the point ) is defined y non-liner function detiled in eqution (1). T y ( e P ) + (1) F( PW ) 1 P e Besides, the orld coordinte system might coincide ith the cmer coordinte system: M K W M K nd K M W K M inv( M K W ). Therefore, eqution (8) cn e ritten s: D W P K K F( inv( K ) P) (11) i M M nd, epnding the mtrices e otin eqution (1):

5 1 F (1) s i α u u 1 Fy s yi αv v 1 t F s Summriing eqution (1), it is ovious tht there re seven unknons: ) the four intrinsic prmeters of the cmer; ) the trnsltion vector corresponding to the trnsformtion mtri eteen the mirror nd the cmer coordinte system; nd c) the nd prmeters tht define the hyperolic shpe of the cmer mirror. The clirtion method otins the vlues of these seven unknons y mens of non-liner minimition of eqution (1) sed on evenerg-mrqurd nd set of knon oject points (clirting pttern). incoming nd outgoing lser rys. The sensor is plced in virtul room hose lls plne equtions re knon. The room is 3 meters nd.5 meters height. At clirtion time, the sensor s plced t 1 meter height from the floor. 3.. The pir lser nd lser mirror. The lser source emits opticl circle forming cone hich is determined y the lser pose nd the perture ngle of the lens. Tht cone is then projected onto the lser mirror tords the 3D scene spreding the light in set of opticl rys. Every opticl ry intersects ith knon clirting plnes otining set of 3D points W P hich re imged y the cmer system. Besides the perture ngle γ is knon nd given y mnufcturers. Then, the reltionship eteen the lser prmeters nd the set of 3D points is determined y eqution (13). tn( γ ) 4 ( e (( + W W ) ( y ) ( W ( e W + df dff (( ) ( ) W W + + W + yw ) ) ) ( + ( y ) y + ) yw ) ) (13) Figure 4. Virtul sensor used for clirtion The coordintes of the points W P re otined from their D projection on the imge plne nd the prmeters of the cmer system given y the clirting lgorithm eplined in section 3.1. Eqution (13) is composed y only four unknons prmeters: ) the mirror shpe prmeters, ; ) dff, the trnsltion eteen the orld coordinte system nd the focl point of the lser mirror nd c) df, the distnce eteen the lser source point nd the focl point of the nd the corresponding mirror. The solution of such non-liner system is lso otined y minimition lgorithm sed on evenerg-mrqurt. A set of itertions hs een provided to the clirting lgorithm considering Gussin noise from σ up to σ in increments of.1. In Figure 5 is presented the discrepncy eteen the 3D oject points (epressed in millimetres) given y the proper model (ith ero noise) ith respect to the model otined y clirtion in the presence of noise. Besides, Figure 6 shos the sme discrepncy ut ith respect to the imge points, represented in piels. 5. EXPERIMENTA RESUTS The hole model presented in section 3 hs een simulted in Mtl ith the im of nlysing the ccurcy of the clirting lgorithm in the presence of Gussin noise. The complete virtul sensor used is shon in figure 3. The reflecting shpes of the to mirrors cn e oserved. The dotted lines represent the Figure 5. Distnce eteen the pttern 3D points nd the reconstructed 3D points y mens of the model otined y clirtion in the presence of noise.

6 Figure 6. Distnce eteen the noiseless imge points nd the reconstructed D points using the model otined y clirtion in the presence of noise. 6. ONUSIONS Pssive stereo ctdioptric sensors re structures uilt in order to provide 3D informtion using pnormic imges. Depth is clculted y tringultion oserving the sme fetures from different points of vie. The min dvntge of such sensors is tht depth is clculted simultneously round field of vie of 36º hich mkes them suitle for rel-time pplictions. Hoever, stereo techniques hve mjor limittion relted to the high computtionl cost of the imge segmenttion stge nd the further mtching solving process. Introducing structured light projection, the oserved points re identified fster. Moreover, y using monochromtic lser projector, the pttern cn e isolted y mens of opticl filters. This pper proposes ne device tht permits the cquisition of three dimensionl informtion from unique imge voiding the correspondence prolem present in most stereo vision systems. Moreover, the use of monochromtic light implies rpid nd ccurte imge segmenttion reducing the computtionl requirements. A set of suitle lenses nd mirror shpes nd severl possile pnormic ctdioptrics sensors re presented nd, finlly, ne stereo ctdioptric sensor sed on lser structured light projection is introduced nd studied. This ork provides etensive informtion on the modelling nd using of such sensors nd represents compulsory step in the designing process. onference on Rootics nd Automtion, pge(s): vol.1, -8, Apr [5] M. Fil, A. Bsu, Feture etrction nd clirtion for stereo reconstruction using non-svp optics in pnormic stereo-vision sensor, Proceedings of the IEEE Workshop on Omni directionl Vision, Pge(s): 79-86,. [6] M. Ollis, H. Hermn nd S. Singh, Anlysis nd Design of Pnormic Stereo Vision Using Equi-Angulr Piel mers, tech. report MU-RI-TR-99-4, Rootics Institute, rnegie Mellon University, Jnury, [7] D. Southell, A. Bsu, M. Fil, M., J. Reyd, Pnormic stereo, Proceedings of the 13th Interntionl onference on Pttern Recognition, Volume: 1, Pge(s): [8] J. Bldin, A. Bsu, 3D Estimtion Using Pnormic Stereo, Proceedings of 15th Interntionl onference on Pttern Recognition, Pge(s): 97-1 vol.1,. [9] J. Gluckmn, S.K. Nyr nd Thores K.J., Rel-Time Omnidirectionl nd Pnormic Stereo, Proceedings of the 1998 DARPA Imge Understnding Workshop, Monterey, liforni, Novemer [1] S.A. Nene, S.K. Nyr, Stereo ith mirrors, Sith Interntionl onference on omputer Vision, Pge(s): , [11] J. Btlle, E. Mouddi nd J. Slvi. A Survey: Recent Progress in oded Structured ight s Technique to Solve the orrespondence Prolem. Pttern Recognition 31(7), pp , July REFERENES [1] S. Bker nd S.K. Nyr, A theory of ctdioptric imge formtion, Sith Interntionl onference on omputer Vision, Pge(s): 35-4, [] K. Ym, Y. Ygi, M. Ychid, Omnidirectionl imging ith hyperoloidl projection, Proceedings of the 1993 IEEE/RSJ Interntionl onference on Intelligent Roots nd Systems '93, Volume:, Pge(s): , 1993 [3] Y. Ygi, M.Ychid, Omnidirectionl Sensing nd Its Applictions, IEIE Trns. Inf. & SYST., Vol.E8-D, No.3, Mrch [4]. Pegrd, E.M. Mouddi, A moile root using pnormic vie,proceedings. of IEEE Interntionl

2 Computing all Intersections of a Set of Segments Line Segment Intersection

2 Computing all Intersections of a Set of Segments Line Segment Intersection 15-451/651: Design & Anlysis of Algorithms Novemer 14, 2016 Lecture #21 Sweep-Line nd Segment Intersection lst chnged: Novemer 8, 2017 1 Preliminries The sweep-line prdigm is very powerful lgorithmic design

More information

CHAPTER III IMAGE DEWARPING (CALIBRATION) PROCEDURE

CHAPTER III IMAGE DEWARPING (CALIBRATION) PROCEDURE CHAPTER III IMAGE DEWARPING (CALIBRATION) PROCEDURE 3.1 Scheimpflug Configurtion nd Perspective Distortion Scheimpflug criterion were found out to be the best lyout configurtion for Stereoscopic PIV, becuse

More information

Tree Structured Symmetrical Systems of Linear Equations and their Graphical Solution

Tree Structured Symmetrical Systems of Linear Equations and their Graphical Solution Proceedings of the World Congress on Engineering nd Computer Science 4 Vol I WCECS 4, -4 October, 4, Sn Frncisco, USA Tree Structured Symmetricl Systems of Liner Equtions nd their Grphicl Solution Jime

More information

Class-XI Mathematics Conic Sections Chapter-11 Chapter Notes Key Concepts

Class-XI Mathematics Conic Sections Chapter-11 Chapter Notes Key Concepts Clss-XI Mthemtics Conic Sections Chpter-11 Chpter Notes Key Concepts 1. Let be fixed verticl line nd m be nother line intersecting it t fixed point V nd inclined to it t nd ngle On rotting the line m round

More information

Objective: Students will understand what it means to describe, graph and write the equation of a parabola. Parabolas

Objective: Students will understand what it means to describe, graph and write the equation of a parabola. Parabolas Pge 1 of 8 Ojective: Students will understnd wht it mens to descrie, grph nd write the eqution of prol. Prols Prol: collection of ll points P in plne tht re the sme distnce from fixed point, the focus

More information

GENERATING ORTHOIMAGES FOR CLOSE-RANGE OBJECTS BY AUTOMATICALLY DETECTING BREAKLINES

GENERATING ORTHOIMAGES FOR CLOSE-RANGE OBJECTS BY AUTOMATICALLY DETECTING BREAKLINES GENEATING OTHOIMAGES FO CLOSE-ANGE OBJECTS BY AUTOMATICALLY DETECTING BEAKLINES Efstrtios Stylinidis 1, Lzros Sechidis 1, Petros Ptis 1, Spiros Sptls 2 Aristotle University of Thessloniki 1 Deprtment of

More information

A multiview 3D modeling system based on stereo vision techniques

A multiview 3D modeling system based on stereo vision techniques Mchine Vision nd Applictions (2005) 16: 148 156 Digitl Oject Identifier (DOI) 10.1007/s00138-004-0165-2 Mchine Vision nd Applictions A multiview 3D modeling system sed on stereo vision techniques Soon-Yong

More information

6.3 Volumes. Just as area is always positive, so is volume and our attitudes towards finding it.

6.3 Volumes. Just as area is always positive, so is volume and our attitudes towards finding it. 6.3 Volumes Just s re is lwys positive, so is volume nd our ttitudes towrds finding it. Let s review how to find the volume of regulr geometric prism, tht is, 3-dimensionl oject with two regulr fces seprted

More information

Stained Glass Design. Teaching Goals:

Stained Glass Design. Teaching Goals: Stined Glss Design Time required 45-90 minutes Teching Gols: 1. Students pply grphic methods to design vrious shpes on the plne.. Students pply geometric trnsformtions of grphs of functions in order to

More information

Modeling and Simulation of Short Range 3D Triangulation-Based Laser Scanning System

Modeling and Simulation of Short Range 3D Triangulation-Based Laser Scanning System Modeling nd Simultion of Short Rnge 3D Tringultion-Bsed Lser Scnning System Theodor Borngiu Anmri Dogr Alexndru Dumitrche April 14, 2008 Abstrct In this pper, simultion environment for short rnge 3D lser

More information

called the vertex. The line through the focus perpendicular to the directrix is called the axis of the parabola.

called the vertex. The line through the focus perpendicular to the directrix is called the axis of the parabola. Review of conic sections Conic sections re grphs of the form REVIEW OF CONIC SECTIONS prols ellipses hperols P(, ) F(, p) O p =_p REVIEW OF CONIC SECTIONS In this section we give geometric definitions

More information

Topics in Analytic Geometry

Topics in Analytic Geometry Nme Chpter 10 Topics in Anltic Geometr Section 10.1 Lines Objective: In this lesson ou lerned how to find the inclintion of line, the ngle between two lines, nd the distnce between point nd line. Importnt

More information

Date: 9.1. Conics: Parabolas

Date: 9.1. Conics: Parabolas Dte: 9. Conics: Prols Preclculus H. Notes: Unit 9 Conics Conic Sections: curves tht re formed y the intersection of plne nd doulenpped cone Syllus Ojectives:. The student will grph reltions or functions,

More information

Fig.1. Let a source of monochromatic light be incident on a slit of finite width a, as shown in Fig. 1.

Fig.1. Let a source of monochromatic light be incident on a slit of finite width a, as shown in Fig. 1. Answer on Question #5692, Physics, Optics Stte slient fetures of single slit Frunhofer diffrction pttern. The slit is verticl nd illuminted by point source. Also, obtin n expression for intensity distribution

More information

Parametric ego-motion estimation for vehicle surround analysis using an omnidirectional camera

Parametric ego-motion estimation for vehicle surround analysis using an omnidirectional camera Mchine Vision nd Applictions (25) 16: 85 95 Digitl Oject Identifier (DOI) 1.17/s138-4-168-z Mchine Vision nd Applictions Prmetric ego-motion estimtion for vehicle surround nlysis using n omnidirectionl

More information

Graphing Conic Sections

Graphing Conic Sections Grphing Conic Sections Definition of Circle Set of ll points in plne tht re n equl distnce, clled the rdius, from fixed point in tht plne, clled the center. Grphing Circle (x h) 2 + (y k) 2 = r 2 where

More information

Section 9.2 Hyperbolas

Section 9.2 Hyperbolas Section 9. Hperols 597 Section 9. Hperols In the lst section, we lerned tht plnets hve pproimtel ellipticl orits round the sun. When n oject like comet is moving quickl, it is le to escpe the grvittionl

More information

Lecture 10 Evolutionary Computation: Evolution strategies and genetic programming

Lecture 10 Evolutionary Computation: Evolution strategies and genetic programming Lecture 10 Evolutionry Computtion: Evolution strtegies nd genetic progrmming Evolution strtegies Genetic progrmming Summry Negnevitsky, Person Eduction, 2011 1 Evolution Strtegies Another pproch to simulting

More information

Analysis of Computed Diffraction Pattern Diagram for Measuring Yarn Twist Angle

Analysis of Computed Diffraction Pattern Diagram for Measuring Yarn Twist Angle Textiles nd Light ndustril Science nd Technology (TLST) Volume 3, 2014 DO: 10.14355/tlist.2014.0301.01 http://www.tlist-journl.org Anlysis of Computed Diffrction Pttern Digrm for Mesuring Yrn Twist Angle

More information

II. THE ALGORITHM. A. Depth Map Processing

II. THE ALGORITHM. A. Depth Map Processing Lerning Plnr Geometric Scene Context Using Stereo Vision Pul G. Bumstrck, Bryn D. Brudevold, nd Pul D. Reynolds {pbumstrck,brynb,pulr2}@stnford.edu CS229 Finl Project Report December 15, 2006 Abstrct A

More information

MTH 146 Conics Supplement

MTH 146 Conics Supplement 105- Review of Conics MTH 146 Conics Supplement In this section we review conics If ou ne more detils thn re present in the notes, r through section 105 of the ook Definition: A prol is the set of points

More information

Study Sheet ( )

Study Sheet ( ) Key Terms prol circle Ellipse hyperol directrix focus focl length xis of symmetry vertex Study Sheet (11.1-11.4) Conic Section A conic section is section of cone. The ellipse, prol, nd hyperol, long with

More information

Lecture 4 Single View Metrology

Lecture 4 Single View Metrology Lecture 4 Single View Metrology Professor Silvio Svrese Computtionl Vision nd Geometry Lb Silvio Svrese Lecture 4-4-Jn-5 Lecture 4 Single View Metrology Review clibrtion nd 2D trnsformtions Vnishing points

More information

A dual of the rectangle-segmentation problem for binary matrices

A dual of the rectangle-segmentation problem for binary matrices A dul of the rectngle-segmenttion prolem for inry mtrices Thoms Klinowski Astrct We consider the prolem to decompose inry mtrix into smll numer of inry mtrices whose -entries form rectngle. We show tht

More information

4452 Mathematical Modeling Lecture 4: Lagrange Multipliers

4452 Mathematical Modeling Lecture 4: Lagrange Multipliers Mth Modeling Lecture 4: Lgrnge Multipliers Pge 4452 Mthemticl Modeling Lecture 4: Lgrnge Multipliers Lgrnge multipliers re high powered mthemticl technique to find the mximum nd minimum of multidimensionl

More information

Cameras. Importance of camera models

Cameras. Importance of camera models pture imges mesuring devie Digitl mers mers fill in memor ith olor-smple informtion D hrge-oupled Devie insted of film film lso hs finite resolution grininess depends on speed IS 00 00 6400 sie 35mm IMAX

More information

Before We Begin. Introduction to Spatial Domain Filtering. Introduction to Digital Image Processing. Overview (1): Administrative Details (1):

Before We Begin. Introduction to Spatial Domain Filtering. Introduction to Digital Image Processing. Overview (1): Administrative Details (1): Overview (): Before We Begin Administrtive detils Review some questions to consider Winter 2006 Imge Enhncement in the Sptil Domin: Bsics of Sptil Filtering, Smoothing Sptil Filters, Order Sttistics Filters

More information

Real-Time Stereo Vision Techniques

Real-Time Stereo Vision Techniques Rel-Time Stereo Vision Techniques Christos Georgouls nd Ionnis Andredis Lortory of Electronics, Deprtment of Electricl nd Computer Engineering Democritus University of Thrce Xnthi 6700, Greece {cgeorg,indred}@ee.duth.gr

More information

The Nature of Light. Light is a propagating electromagnetic waves

The Nature of Light. Light is a propagating electromagnetic waves The Nture of Light Light is propgting electromgnetic wves Index of Refrction n: In mterils, light intercts with toms/molecules nd trvels slower thn it cn in vcuum, e.g., vwter The opticl property of trnsprent

More information

Section 10.4 Hyperbolas

Section 10.4 Hyperbolas 66 Section 10.4 Hyperbols Objective : Definition of hyperbol & hyperbols centered t (0, 0). The third type of conic we will study is the hyperbol. It is defined in the sme mnner tht we defined the prbol

More information

COLOUR IMAGE MATCHING FOR DTM GENERATION AND HOUSE EXTRACTION

COLOUR IMAGE MATCHING FOR DTM GENERATION AND HOUSE EXTRACTION Hee Ju Prk OLOUR IMAGE MATHING FOR DTM GENERATION AND HOUSE EXTRATION Hee Ju PARK, Petr ZINMMERMANN * Swiss Federl Institute of Technology, Zuric Switzerlnd Institute for Geodesy nd Photogrmmetry heeju@ns.shingu-c.c.kr

More information

On the Detection of Step Edges in Algorithms Based on Gradient Vector Analysis

On the Detection of Step Edges in Algorithms Based on Gradient Vector Analysis On the Detection of Step Edges in Algorithms Bsed on Grdient Vector Anlysis A. Lrr6, E. Montseny Computer Engineering Dept. Universitt Rovir i Virgili Crreter de Slou sin 43006 Trrgon, Spin Emil: lrre@etse.urv.es

More information

A TRIANGULAR FINITE ELEMENT FOR PLANE ELASTICITY WITH IN- PLANE ROTATION Dr. Attia Mousa 1 and Eng. Salah M. Tayeh 2

A TRIANGULAR FINITE ELEMENT FOR PLANE ELASTICITY WITH IN- PLANE ROTATION Dr. Attia Mousa 1 and Eng. Salah M. Tayeh 2 A TRIANGLAR FINITE ELEMENT FOR PLANE ELASTICITY WITH IN- PLANE ROTATION Dr. Atti Mous nd Eng. Slh M. Teh ABSTRACT In the present pper the strin-bsed pproch is pplied to develop new tringulr finite element

More information

TOWARDS GRADIENT BASED AERODYNAMIC OPTIMIZATION OF WIND TURBINE BLADES USING OVERSET GRIDS

TOWARDS GRADIENT BASED AERODYNAMIC OPTIMIZATION OF WIND TURBINE BLADES USING OVERSET GRIDS TOWARDS GRADIENT BASED AERODYNAMIC OPTIMIZATION OF WIND TURBINE BLADES USING OVERSET GRIDS S. H. Jongsm E. T. A. vn de Weide H. W. M. Hoeijmkers Overset symposium 10-18-2012 Deprtment of mechnicl engineering

More information

What are suffix trees?

What are suffix trees? Suffix Trees 1 Wht re suffix trees? Allow lgorithm designers to store very lrge mount of informtion out strings while still keeping within liner spce Allow users to serch for new strings in the originl

More information

AML710 CAD LECTURE 16 SURFACES. 1. Analytical Surfaces 2. Synthetic Surfaces

AML710 CAD LECTURE 16 SURFACES. 1. Analytical Surfaces 2. Synthetic Surfaces AML7 CAD LECTURE 6 SURFACES. Anlticl Surfces. Snthetic Surfces Surfce Representtion From CAD/CAM point of view surfces re s importnt s curves nd solids. We need to hve n ide of curves for surfce cretion.

More information

Spectral Analysis of MCDF Operations in Image Processing

Spectral Analysis of MCDF Operations in Image Processing Spectrl Anlysis of MCDF Opertions in Imge Processing ZHIQIANG MA 1,2 WANWU GUO 3 1 School of Computer Science, Northest Norml University Chngchun, Jilin, Chin 2 Deprtment of Computer Science, JilinUniversity

More information

Machine vision system for surface inspection on brushed industrial parts.

Machine vision system for surface inspection on brushed industrial parts. Mchine vision system for surfce inspection on rushed industril prts. Nicols Bonnot, Rlph Seulin, Frederic Merienne Lortoire Le2i, CNRS UMR 5158, University of Burgundy, Le Creusot, Frnce. ABSTRACT This

More information

1. SEQUENCES INVOLVING EXPONENTIAL GROWTH (GEOMETRIC SEQUENCES)

1. SEQUENCES INVOLVING EXPONENTIAL GROWTH (GEOMETRIC SEQUENCES) Numbers nd Opertions, Algebr, nd Functions 45. SEQUENCES INVOLVING EXPONENTIAL GROWTH (GEOMETRIC SEQUENCES) In sequence of terms involving eponentil growth, which the testing service lso clls geometric

More information

USING HOUGH TRANSFORM IN LINE EXTRACTION

USING HOUGH TRANSFORM IN LINE EXTRACTION Stylinidis, Efstrtios USING HOUGH TRANSFORM IN LINE EXTRACTION Efstrtios STYLIANIDIS, Petros PATIAS The Aristotle University of Thessloniki, Deprtment of Cdstre Photogrmmetry nd Crtogrphy Univ. Box 473,

More information

Motion analysis for event detection and tracking with a mobile omnidirectional camera

Motion analysis for event detection and tracking with a mobile omnidirectional camera Multimedi Systems 10: 131 143 (2004) Digitl Oject Identifier (DOI) 10.1007/s00530-004-0146-3 Multimedi Systems Motion nlysis for event detection nd trcking with moile omnidirectionl cmer Trk Gndhi, Mohn

More information

Paracatadioptric Camera Calibration Using Lines

Paracatadioptric Camera Calibration Using Lines Prctdioptric Cmer Clibrtion Using Lines Joo P Brreto, Helder Arujo Institute of Systems nd Robotics - Dept of Electricl nd Computer Engineering University of Coimbr, Coimbr, Portugl Abstrct Prctdioptric

More information

Power Transmittance of a Laterally Shifted Gaussian Beam through a Circular Aperture

Power Transmittance of a Laterally Shifted Gaussian Beam through a Circular Aperture Poer Trnsmittnce of Lterlly Shifted Gussin Bem through Circulr Aperture Triq Shmim Khj 1 nd Syed Azer Rez 1 1. Deprtment of Electricl Engineering, Lhore University of Mngement Sciences, DHA, Lhore 5479,

More information

LETKF compared to 4DVAR for assimilation of surface pressure observations in IFS

LETKF compared to 4DVAR for assimilation of surface pressure observations in IFS LETKF compred to 4DVAR for ssimiltion of surfce pressure oservtions in IFS Pu Escrià, Mssimo Bonvit, Mts Hmrud, Lrs Isksen nd Pul Poli Interntionl Conference on Ensemle Methods in Geophysicl Sciences Toulouse,

More information

International Conference on Mechanics, Materials and Structural Engineering (ICMMSE 2016)

International Conference on Mechanics, Materials and Structural Engineering (ICMMSE 2016) \ Interntionl Conference on Mechnics, Mterils nd tructurl Engineering (ICMME 2016) Reserch on the Method to Clibrte tructure Prmeters of Line tructured Light Vision ensor Mingng Niu1,, Kngnin Zho1, b,

More information

8.2 Areas in the Plane

8.2 Areas in the Plane 39 Chpter 8 Applictions of Definite Integrls 8. Ares in the Plne Wht ou will lern out... Are Between Curves Are Enclosed Intersecting Curves Boundries with Chnging Functions Integrting with Respect to

More information

Optics and Optical design Problems

Optics and Optical design Problems Optics nd Opticl design 0 Problems Sven-Görn Pettersson / Cord Arnold 0-09-06 4:3 This mteril is tken from severl sources. Some problems re from the book Våglär och Optik by Görn Jönsson nd Elisbeth Nilsson.

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION Supplementry Figure y (m) x (m) prllel perpendiculr Distnce (m) Bird Stndrd devition for distnce (m) c 6 prllel perpendiculr 4 doi:.8/nture99 SUPPLEMENTARY FIGURE Confirmtion tht movement within the flock

More information

Hyperbolas. Definition of Hyperbola

Hyperbolas. Definition of Hyperbola CHAT Pre-Clculus Hyperols The third type of conic is clled hyperol. For n ellipse, the sum of the distnces from the foci nd point on the ellipse is fixed numer. For hyperol, the difference of the distnces

More information

If you are at the university, either physically or via the VPN, you can download the chapters of this book as PDFs.

If you are at the university, either physically or via the VPN, you can download the chapters of this book as PDFs. Lecture 5 Wlks, Trils, Pths nd Connectedness Reding: Some of the mteril in this lecture comes from Section 1.2 of Dieter Jungnickel (2008), Grphs, Networks nd Algorithms, 3rd edition, which is ville online

More information

1.1. Interval Notation and Set Notation Essential Question When is it convenient to use set-builder notation to represent a set of numbers?

1.1. Interval Notation and Set Notation Essential Question When is it convenient to use set-builder notation to represent a set of numbers? 1.1 TEXAS ESSENTIAL KNOWLEDGE AND SKILLS Prepring for 2A.6.K, 2A.7.I Intervl Nottion nd Set Nottion Essentil Question When is it convenient to use set-uilder nottion to represent set of numers? A collection

More information

Computer Vision and Image Understanding

Computer Vision and Image Understanding Computer Vision nd Imge Understnding 116 (2012) 25 37 Contents lists ville t SciVerse ScienceDirect Computer Vision nd Imge Understnding journl homepge: www.elsevier.com/locte/cviu A systemtic pproch for

More information

Naming 3D objects. 1 Name the 3D objects labelled in these models. Use the word bank to help you.

Naming 3D objects. 1 Name the 3D objects labelled in these models. Use the word bank to help you. Nming 3D ojects 1 Nme the 3D ojects lelled in these models. Use the word nk to help you. Word nk cue prism sphere cone cylinder pyrmid D A C F A B C D cone cylinder cue cylinder E B E prism F cue G G pyrmid

More information

Paracatadioptric Camera Calibration Using Lines

Paracatadioptric Camera Calibration Using Lines Prctdioptric Cmer Clibrtion Using Lines Joo P Brreto, Helder Arujo Institute of Systems nd Robotics - Dept of Electricl nd Computer Engineering University of Coimbr, 33 Coimbr, Portugl Abstrct Prctdioptric

More information

Video-rate Image Segmentation by means of Region Splitting and Merging

Video-rate Image Segmentation by means of Region Splitting and Merging Video-rte Imge Segmenttion y mens of Region Splitting nd Merging Knur Anej, Florence Lguzet, Lionel Lcssgne, Alin Merigot Institute for Fundmentl Electronics, University of Pris South Orsy, Frnce knur.nej@gmil.com,

More information

The notation y = f(x) gives a way to denote specific values of a function. The value of f at a can be written as f( a ), read f of a.

The notation y = f(x) gives a way to denote specific values of a function. The value of f at a can be written as f( a ), read f of a. Chpter Prerequisites for Clculus. Functions nd Grphs Wht ou will lern out... Functions Domins nd Rnges Viewing nd Interpreting Grphs Even Functions nd Odd Functions Smmetr Functions Defined in Pieces Asolute

More information

OPTICS. (b) 3 3. (d) (c) , A small piece

OPTICS. (b) 3 3. (d) (c) , A small piece AQB-07-P-106 641. If the refrctive indices of crown glss for red, yellow nd violet colours re 1.5140, 1.5170 nd 1.518 respectively nd for flint glss re 1.644, 1.6499 nd 1.685 respectively, then the dispersive

More information

A Study on Eye Gaze Estimation Method Based on Cornea Model of Human Eye

A Study on Eye Gaze Estimation Method Based on Cornea Model of Human Eye A Study on Eye Gze Estimtion Method Bsed on Corne Model of Humn Eye Eui Chul Lee 1 nd Kng Ryoung Prk 2 1 Dept. of Computer Science, Sngmyung University, 7 Hongji-dong, Jongro-Ku, Seoul, Republic of Kore

More information

4-1 NAME DATE PERIOD. Study Guide. Parallel Lines and Planes P Q, O Q. Sample answers: A J, A F, and D E

4-1 NAME DATE PERIOD. Study Guide. Parallel Lines and Planes P Q, O Q. Sample answers: A J, A F, and D E 4-1 NAME DATE PERIOD Pges 142 147 Prllel Lines nd Plnes When plnes do not intersect, they re sid to e prllel. Also, when lines in the sme plne do not intersect, they re prllel. But when lines re not in

More information

Presentation Martin Randers

Presentation Martin Randers Presenttion Mrtin Rnders Outline Introduction Algorithms Implementtion nd experiments Memory consumption Summry Introduction Introduction Evolution of species cn e modelled in trees Trees consist of nodes

More information

Slides for Data Mining by I. H. Witten and E. Frank

Slides for Data Mining by I. H. Witten and E. Frank Slides for Dt Mining y I. H. Witten nd E. Frnk Simplicity first Simple lgorithms often work very well! There re mny kinds of simple structure, eg: One ttriute does ll the work All ttriutes contriute eqully

More information

Rigid Body Transformations

Rigid Body Transformations igid od Kinemtics igid od Trnsformtions Vij Kumr igid od Kinemtics emrk out Nottion Vectors,,, u, v, p, q, Potentil for Confusion! Mtrices,, C, g, h, igid od Kinemtics The vector nd its skew smmetric mtri

More information

Complete Coverage Path Planning of Mobile Robot Based on Dynamic Programming Algorithm Peng Zhou, Zhong-min Wang, Zhen-nan Li, Yang Li

Complete Coverage Path Planning of Mobile Robot Based on Dynamic Programming Algorithm Peng Zhou, Zhong-min Wang, Zhen-nan Li, Yang Li 2nd Interntionl Conference on Electronic & Mechnicl Engineering nd Informtion Technology (EMEIT-212) Complete Coverge Pth Plnning of Mobile Robot Bsed on Dynmic Progrmming Algorithm Peng Zhou, Zhong-min

More information

15. 3D-Reconstruction from Vanishing Points

15. 3D-Reconstruction from Vanishing Points 15. 3D-Reconstruction from Vnishing Points Christin B.U. Perwss 1 nd Jon Lseny 2 1 Cvendish Lortory, Cmridge 2 C. U. Engineering Deprtment, Cmridge 15.1 Introduction 3D-reconstruction is currently n ctive

More information

Fig.25: the Role of LEX

Fig.25: the Role of LEX The Lnguge for Specifying Lexicl Anlyzer We shll now study how to uild lexicl nlyzer from specifiction of tokens in the form of list of regulr expressions The discussion centers round the design of n existing

More information

A Tautology Checker loosely related to Stålmarck s Algorithm by Martin Richards

A Tautology Checker loosely related to Stålmarck s Algorithm by Martin Richards A Tutology Checker loosely relted to Stålmrck s Algorithm y Mrtin Richrds mr@cl.cm.c.uk http://www.cl.cm.c.uk/users/mr/ University Computer Lortory New Museum Site Pemroke Street Cmridge, CB2 3QG Mrtin

More information

Here is an example where angles with a common arm and vertex overlap. Name all the obtuse angles adjacent to

Here is an example where angles with a common arm and vertex overlap. Name all the obtuse angles adjacent to djcent tht do not overlp shre n rm from the sme vertex point re clled djcent ngles. me the djcent cute ngles in this digrm rm is shred y + + me vertex point for + + + is djcent to + djcent simply mens

More information

The gamuts of input and output colour imaging media

The gamuts of input and output colour imaging media In Proceedings of IS&T/SPIE Electronic Imging 1 The gmuts of input nd output colour imging medi án Morovic,* Pei Li Sun* nd Peter Morovic * Colour & Imging Institute, University of Dery, UK School of Informtion

More information

9.1 apply the distance and midpoint formulas

9.1 apply the distance and midpoint formulas 9.1 pply the distnce nd midpoint formuls DISTANCE FORMULA MIDPOINT FORMULA To find the midpoint between two points x, y nd x y 1 1,, we Exmple 1: Find the distnce between the two points. Then, find the

More information

Chapter44. Polygons and solids. Contents: A Polygons B Triangles C Quadrilaterals D Solids E Constructing solids

Chapter44. Polygons and solids. Contents: A Polygons B Triangles C Quadrilaterals D Solids E Constructing solids Chpter44 Polygons nd solids Contents: A Polygons B Tringles C Qudrilterls D Solids E Constructing solids 74 POLYGONS AND SOLIDS (Chpter 4) Opening prolem Things to think out: c Wht different shpes cn you

More information

Ranking of Hexagonal Fuzzy Numbers for Solving Multi Objective Fuzzy Linear Programming Problem

Ranking of Hexagonal Fuzzy Numbers for Solving Multi Objective Fuzzy Linear Programming Problem Interntionl Journl of Computer pplictions 097 8887 Volume 8 No 8 Decemer 0 nking of egonl Fuzzy Numers Solving ulti Ojective Fuzzy Liner Progrmming Prolem jrjeswri. P Deprtment of themtics Chikknn Government

More information

50 AMC LECTURES Lecture 2 Analytic Geometry Distance and Lines. can be calculated by the following formula:

50 AMC LECTURES Lecture 2 Analytic Geometry Distance and Lines. can be calculated by the following formula: 5 AMC LECTURES Lecture Anlytic Geometry Distnce nd Lines BASIC KNOWLEDGE. Distnce formul The distnce (d) between two points P ( x, y) nd P ( x, y) cn be clculted by the following formul: d ( x y () x )

More information

PRISMS. Don t see exactly what you are looking for? CVI Laser Optics specializes in prototype to volume production manufacturing!

PRISMS. Don t see exactly what you are looking for? CVI Laser Optics specializes in prototype to volume production manufacturing! PRISMS Mirrors CVI Lser Optics mnufctures lrge selection of high qulity prisms for use in mny pplictions including diverse industril nd scientific uses, lser trcking nd lignment, spectroscopy, nd militry

More information

Lecture 5: Spatial Analysis Algorithms

Lecture 5: Spatial Analysis Algorithms Lecture 5: Sptil Algorithms GEOG 49: Advnced GIS Sptil Anlsis Algorithms Bsis of much of GIS nlsis tod Mnipultion of mp coordintes Bsed on Eucliden coordinte geometr http://stronom.swin.edu.u/~pbourke/geometr/

More information

Tilt-Sensing with Kionix MEMS Accelerometers

Tilt-Sensing with Kionix MEMS Accelerometers Tilt-Sensing with Kionix MEMS Accelerometers Introduction Tilt/Inclintion sensing is common ppliction for low-g ccelerometers. This ppliction note describes how to use Kionix MEMS low-g ccelerometers to

More information

ZZ - Advanced Math Review 2017

ZZ - Advanced Math Review 2017 ZZ - Advnced Mth Review Mtrix Multipliction Given! nd! find the sum of the elements of the product BA First, rewrite the mtrices in the correct order to multiply The product is BA hs order x since B is

More information

Algorithm Design (5) Text Search

Algorithm Design (5) Text Search Algorithm Design (5) Text Serch Tkshi Chikym School of Engineering The University of Tokyo Text Serch Find sustring tht mtches the given key string in text dt of lrge mount Key string: chr x[m] Text Dt:

More information

Essential Question What are some of the characteristics of the graph of a rational function?

Essential Question What are some of the characteristics of the graph of a rational function? 8. TEXAS ESSENTIAL KNOWLEDGE AND SKILLS A..A A..G A..H A..K Grphing Rtionl Functions Essentil Question Wht re some of the chrcteristics of the grph of rtionl function? The prent function for rtionl functions

More information

Image Segmentation Using Wavelet and watershed transform

Image Segmentation Using Wavelet and watershed transform Imge Segmenttion Using Wvelet nd wtershed trnsform Atollh Hdddi, Mhmod R. Shei, Mohmmd J. Vldn Zoej, Ali mohmmdzdeh Fculty of Geodesy nd Geomtics Engineering, K. N. Toosi University of Technology, Vli_Asr

More information

Subband coding of image sequences using multiple vector quantizers. Emanuel Martins, Vitor Silva and Luís de Sá

Subband coding of image sequences using multiple vector quantizers. Emanuel Martins, Vitor Silva and Luís de Sá Sund coding of imge sequences using multiple vector quntizers Emnuel Mrtins, Vitor Silv nd Luís de Sá Instituto de Telecomunicções, Deprtmento de Engenhri Electrotécnic Pólo II d Universidde de Coimr,

More information

2 Surface Topology. 2.1 Topological Type. Computational Topology Surface Topology Afra Zomorodian

2 Surface Topology. 2.1 Topological Type. Computational Topology Surface Topology Afra Zomorodian Klein ottle for rent inquire ithin. Anonymous 2 Surfce Topology Lst lecture, e spent considerle mount of effort defining mnifolds. We like mnifolds ecuse they re loclly Eucliden. So, een though it is hrd

More information

Math 35 Review Sheet, Spring 2014

Math 35 Review Sheet, Spring 2014 Mth 35 Review heet, pring 2014 For the finl exm, do ny 12 of the 15 questions in 3 hours. They re worth 8 points ech, mking 96, with 4 more points for netness! Put ll your work nd nswers in the provided

More information

this grammar generates the following language: Because this symbol will also be used in a later step, it receives the

this grammar generates the following language: Because this symbol will also be used in a later step, it receives the LR() nlysis Drwcks of LR(). Look-hed symols s eplined efore, concerning LR(), it is possile to consult the net set to determine, in the reduction sttes, for which symols it would e possile to perform reductions.

More information

Conic Sections Parabola Objective: Define conic section, parabola, draw a parabola, standard equations and their graphs

Conic Sections Parabola Objective: Define conic section, parabola, draw a parabola, standard equations and their graphs Conic Sections Prol Ojective: Define conic section, prol, drw prol, stndrd equtions nd their grphs The curves creted y intersecting doule npped right circulr cone with plne re clled conic sections. If

More information

Network Layer: Routing Classifications; Shortest Path Routing

Network Layer: Routing Classifications; Shortest Path Routing igitl ommuniction in the Modern World : Routing lssifictions; Shortest Pth Routing s min prolem: To get efficiently from one point to the other in dynmic environment http://.cs.huji.c.il/~com com@cs.huji.c.il

More information

Chapter 2 Sensitivity Analysis: Differential Calculus of Models

Chapter 2 Sensitivity Analysis: Differential Calculus of Models Chpter 2 Sensitivity Anlysis: Differentil Clculus of Models Abstrct Models in remote sensing nd in science nd engineering, in generl re, essentilly, functions of discrete model input prmeters, nd/or functionls

More information

An Expressive Hybrid Model for the Composition of Cardinal Directions

An Expressive Hybrid Model for the Composition of Cardinal Directions An Expressive Hyrid Model for the Composition of Crdinl Directions Ah Lin Kor nd Brndon Bennett School of Computing, University of Leeds, Leeds LS2 9JT, UK e-mil:{lin,brndon}@comp.leeds.c.uk Astrct In

More information

Mathematics Background

Mathematics Background For more roust techer experience, plese visit Techer Plce t mthdshord.com/cmp3 Mthemtics Bckground Extending Understnding of Two-Dimensionl Geometry In Grde 6, re nd perimeter were introduced to develop

More information

COMP 423 lecture 11 Jan. 28, 2008

COMP 423 lecture 11 Jan. 28, 2008 COMP 423 lecture 11 Jn. 28, 2008 Up to now, we hve looked t how some symols in n lphet occur more frequently thn others nd how we cn sve its y using code such tht the codewords for more frequently occuring

More information

EXPONENTIAL & POWER GRAPHS

EXPONENTIAL & POWER GRAPHS Eponentil & Power Grphs EXPONENTIAL & POWER GRAPHS www.mthletics.com.u Eponentil EXPONENTIAL & Power & Grphs POWER GRAPHS These re grphs which result from equtions tht re not liner or qudrtic. The eponentil

More information

Object and image indexing based on region connection calculus and oriented matroid theory

Object and image indexing based on region connection calculus and oriented matroid theory Discrete Applied Mthemtics 147 (2005) 345 361 www.elsevier.com/locte/dm Oject nd imge indexing sed on region connection clculus nd oriented mtroid theory Ernesto Stffetti, Antoni Gru, Frncesc Serrtos c,

More information

Slicer Method Comparison Using Open-source 3D Printer

Slicer Method Comparison Using Open-source 3D Printer IOP Conference Series: Erth nd Environmentl Science PAPER OPEN ACCESS Slicer Method Comprison Using Open-source 3D Printer To cite this rticle: M K A Mohd Ariffin et l 2018 IOP Conf. Ser.: Erth Environ.

More information

1.5 Extrema and the Mean Value Theorem

1.5 Extrema and the Mean Value Theorem .5 Extrem nd the Men Vlue Theorem.5. Mximum nd Minimum Vlues Definition.5. (Glol Mximum). Let f : D! R e function with domin D. Then f hs n glol mximum vlue t point c, iff(c) f(x) for ll x D. The vlue

More information

Introduction Transformation formulae Polar graphs Standard curves Polar equations Test GRAPHS INU0114/514 (MATHS 1)

Introduction Transformation formulae Polar graphs Standard curves Polar equations Test GRAPHS INU0114/514 (MATHS 1) POLAR EQUATIONS AND GRAPHS GEOMETRY INU4/54 (MATHS ) Dr Adrin Jnnett MIMA CMth FRAS Polr equtions nd grphs / 6 Adrin Jnnett Objectives The purpose of this presenttion is to cover the following topics:

More information

Control Camera and Light Source Positions using Image Gradient Information

Control Camera and Light Source Positions using Image Gradient Information IEEE Int. Conf. on Rootics nd Automtion, ICRA'7 Rom, Itli, April 27 Control Cmer nd Light Source Positions using Imge Grdient Informtion Eric Mrchnd Astrct In this pper, we propose n originl pproch to

More information

Extension of the compressed interferometric particle sizing technique for three component velocity measurements

Extension of the compressed interferometric particle sizing technique for three component velocity measurements Lison, Portugl, -9 June, Extension of the compressed interferometric prticle sizing technique for three component velocity mesurements Disuke Sugimoto 1, Konstntinos Zrogoulidis, Ttsuy Kwguchi 3, Kzuki

More information

INVESTIGATION OF RESAMPLING EFFECTS ON IRS-1D PAN DATA

INVESTIGATION OF RESAMPLING EFFECTS ON IRS-1D PAN DATA INVESTIGATION OF RESAMPLING EFFECTS ON IRS-D PAN DATA Smpth Kumr P.,*, Onkr Dikshit nd YVS Murthy Geo-Informtics Division, Ntionl Remote Sensing Agency, Hyderd, Indi.-(smpth_k, murthy_yvs)@nrs.gov.in Deprtment

More information

Semi-Automatic Technique for 3D Building Model Generation

Semi-Automatic Technique for 3D Building Model Generation Ngw El-ASHMAWY, Egypt Key words: DTM, DSM, 3D Building Model, Phoogrmmetry, Remote Sensing. SUMMARY Three Dimensionl Building models re excessively used in vrious pplictions. Digitl Surfce Model is the

More information

MATH 2530: WORKSHEET 7. x 2 y dz dy dx =

MATH 2530: WORKSHEET 7. x 2 y dz dy dx = MATH 253: WORKSHT 7 () Wrm-up: () Review: polr coordintes, integrls involving polr coordintes, triple Riemnn sums, triple integrls, the pplictions of triple integrls (especilly to volume), nd cylindricl

More information

Automated Stereo Camera Calibration System

Automated Stereo Camera Calibration System Automted Stereo Cmer Clibrtion System Brin J O Kennedy, Ben Herbst Deprtment of Electronic Engineering, niversity of Stellenbosch, Stellenbosch, 7, South Afric, brokenn@dspsuncz, herbst@ibissuncz Abstrct

More information