EE 584 MACHINE VISION

Transcription

1 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 EE 584 MACHINE VISION Itroductio elatio with other areas Image Formatio & Sesig Projectios Brightess Leses Image Sesig METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Itroductio Visio is the most powerful sese Visio is the most complicated sese The purpose of a geeral machie/computer/robot visio system is to produce a symbolic descriptio of what is beig imaged.

2 Machie Visio System METU EE 584 Lecture Notes by A.Aydi ALATAN 0 A typical machie visio system : Imagig Device MACHINE VISION Scee Image Descriptio Illumiatio Applicatio Feedback Machie visio should be based o complete uderstadig of image formatio 3 elatio to other fields : 4 importat related fields : METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Imagig (sciece o creatig all kids of images) Image processig Patter recogitio Scee aalysis Image Patter Scee Iput Image Processig Output Image Feature Vector ecogitio Class ID Iput Descriptio Aalysis Output Descriptio Noe of them provides a solutio to the problem developig symbolic descriptios from images. 4

3 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 elatio to other fields : Machie visio vs Computer visio: Two terms ca be used iterchageably Machie visio more costraits o the eviromet ad focus o (idustrial) applicatios Computer visio more geeric i terms of cotet ad applicatios This course is about fudametals of visio research Image from 5 Visio ad Graphics METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Images Visio Model Graphics Iverse problems: aalysis ad sythesis. slide from Computer Visio Lecture Notes Trevor Darrell 6 3

4 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Image Formatio Projectio of 3-D world oto -D image plae Two crucial questios : What determies the positio of a 3-D object poit o the -D image plae? What determies the brightess of a 3-D object poit o the -D image plae? 7 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Image Formatio slide from Computer Visio Lecture Notes Trevor Darrell 8 4

5 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Camera Models Pihole camera model 9 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Camera Models Pihole camera model X x f, y f Y 0 5

6 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Camera Models I pi-hole camera, distat objects are observed smaller B C Camera Models METU EE 584 Lecture Notes by A.Aydi ALATAN 0 I pi-hole camera, parallel lies meet 6

7 Perspective Projectio X x f, y METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Pi-hole camera model is called perspective projectio f Y It is also possible to make approximatios to perspective projectio Affie : Scee poits are plaar Weak-perspective : Scee is approximated by a plae ad assumed to be far away from camera Orthographic : Scee is approximated to be plaar ad far away from camera ad camera distace does ot chage 3 Affie Projectio If all scee poits are o a plae METU EE 584 Lecture Notes by A.Aydi ALATAN 0 X Y f x f, y f m x m X, y my 4 7

8 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Weak-perspective Projectio Now, assume all scee poits are o a plae 0 X Y x f, y f x m X, 0 0 y my This assumptio ca oly be justified, if scee depth rage is small compared to average distace from camera z is small wrt 0 5 Orthographic Projectio METU EE 584 Lecture Notes by A.Aydi ALATAN 0 If scee depth rage is small wrt average depth ad camera distace remai at a costat distace (i.e. 0 is cotat) Choose m- xx, yy 6 8

9 Projectios : Summary Perspective : x x f, y f z y z f (x,y ) METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Y 0 (x,y,z) Orthographic : x x, y y (x,y ) X y (x,y,z) X Perspective projectio is a more realistic projectio for (pi-hole) camera recordigs If depth rage is small compared to average distace from the camera, orthographic is also a good approximatio 7 Brightess : METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Two differet brightess cocepts : Image brightess : irradiace Light power per uit area fallig o a (image) surface Scee brightess : radiace Light power per uit area emitted ito a solid agle from a (object) surface Image ad scee brightess are proportioal to each other Pihole camera eeds o-zero diameter for eough light 8 9

10 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Leses : A pi-hole camera eeds light 9 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Leses : Paraxial (or first-order) optics h h α β + γ + d h h α γ β d Sell s law: si α si α Small agles: α α h h h + d d + d h d Note that the relatio is idepedet of β ad β all rays pass from P, also pass P. slide from Computer Visio Lecture Notes by Marc Pollefeys 0 0

11 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Leses : slide from Computer Visio Lecture Notes by Marc Pollefeys Thi Leses ) ( ad ' f f z z * + + ' * * ' spherical les surfaces; icomig light ± parallel to axis; thickess << radii; same refractive idex o both sides ' * d d + * * METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Leses : A ideal thi les produces the same projectio with a pihole camera, plus some fiite amout of light. z -z Oce you focus for oe distace z, poits o other distaces will be blurred. f z z +

12 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Leses : Deviatios from the les model 3 assumptios :. all rays from a poit are focused oto image poit. all image poits i a sigle plae 3. magificatio is costat deviatios from this ideal are aberratios types of aberratios: geometrical : small for paraxial rays study through 3 rd order optics chromatic : refractive idex fuctio of wavelegth METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Leses : Vigettig: Brightess drop i image periphery for compoud leses Figure from

13 Camera Field of View METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Agular measure of the portio of 3D space see by the camera α arcta(d / F) Image from 5 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Image Sesig : Light photos strikig a suitable (vacuum or semicoductor device) surface geerate electro-hole pairs which are measured to determie the irradiace. Quatum efficiecy : ratio of electro flux to icidet photo flux & depeds o eergy (wavelegth) of photo Solid-state devices almost ideal for some wavelegths Photographic films have poor quatum efficiecy 6 3

14 Quatizatio of Image METU EE 584 Lecture Notes by A.Aydi ALATAN 0 Electros should be measured/averaged at some predefied regios o the image sesor -> Spatial quatizatio These regios ca be square, rectagular or hexagoal Each predefied regio represets a pixel (picture elemet) locatio ad the quatized values are pixel values (usually 0 to 55) 7 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 The Huma Eye eproduced by permissio, the America Society of Photogrammetry ad emote Sesig. A.L. Nowicki, Stereoscopy. Maual of Photogrammetry, Thompso, adliski, ad Speert (eds.), third editio, 966. Helmoltz s Schematic Eye 8 4

15 METU EE 584 Lecture Notes by A.Aydi ALATAN 0 The distributio of rods ad coes across the retia eprited from Foudatios of Visio, by B. Wadell, Siauer Associates, Ic., (995). 995 Siauer Associates, Ic. Coes i the fovea ods ad coes i the periphery 3 types of coes that yield color perceptio eprited from Foudatios of Visio, by B. Wadell, Siauer Associates, Ic., (995). 995 Siauer Associates, Ic. 9 5