cpsc 643 robot vision

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CPSC 643 ROBOT VISION Introduction to Computer Vision Dezhen Song, Department Computer Science and Engineering Texas A&M University Part of slides are from Bahadir K. Gunturk’s EE4780

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CPSC 643 Robot Vision. Introduction to Computer Vision Dezhen Song, Department Computer Science and Engineering Texas A&M University Part of slides are from Bahadir K. Gunturk’s EE4780. Digital Image Acquisition. Imaging Sensors. Charge-Coupled Device (CCD) . Imaging Sensors. - PowerPoint PPT Presentation

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Page 1: CPSC 643 Robot Vision

CPSC 643 ROBOT VISION

Introduction to Computer VisionDezhen Song,

Department Computer Science and EngineeringTexas A&M University

Part of slides are from Bahadir K. Gunturk’s EE4780

Page 2: CPSC 643 Robot Vision

Digital Image Acquisition

Page 3: CPSC 643 Robot Vision

Imaging Sensors Charge-Coupled Device (CCD)

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Imaging Sensors Complementary Metal Oxide

Semiconductor (CMOS)

Page 5: CPSC 643 Robot Vision

CCD Vs. CMOS Responsivity: CMOS >CCD Dynamic range: CCD is 2 times better Uniformity: CCD > CMOS Shuttering

CCD: synchronous shutter (better) CMOS: rolling shutter

Speed: CMOS >> CCD Reliability: CMOS >>CCD Cost: CMOS < CCD

Page 6: CPSC 643 Robot Vision

Bahadir K. Gunturk 6

Matrix Representation of Images

A digital image can be written as a matrix

1 2

[0,0] [0,1] [0, 1][1,0] [1,1] [1, 1]

[ , ]

[ 1,0] [ 1, 1] MxN

x x x Nx x x N

x n n

x M x M N

35 45 2043 64 5210 29 39

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RGB Color Model

Page 8: CPSC 643 Robot Vision

Dynamic range (Contrast Ratio)

Nature light: 1010:1 Human eye: 109:1 CMOS Sensor: 11000-6000:1 LCD panel: 1000-10000:1

Page 9: CPSC 643 Robot Vision

Measured Dynamic Range

Bit Precisionof A/D Converter Contrast Ratio

8 256:110 1024:112 4096:114 16384:116 65536:1

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10

ExposuresLong exposure time

Short exposure time

Page 11: CPSC 643 Robot Vision

Cameras 2D camera (i.e. surveillance camera)

Pin-hole camera Surveillance camera Robotic pan-tilt-zoom camera Wide angle camera –

fisheye, omni, etc 1D camera (satellite camera, scanner) Photo cell

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12

Perspective Projection Perspective projection equations

' ' 'x y zx y z

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13

Pinhole Camera Model

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Cameras With Lenses Most cameras are equipped with lenses. There are two main reasons for this:

To gather light. To keep the picture in sharp focus while gathering

light from a large area.

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Real Lenses Rays may not focus at a single point.

Spherical aberration

Spherical aberration can be eliminated completely by designing aspherical lenses.

Page 16: CPSC 643 Robot Vision

Bahadir K. Gunturk 16

Real Lenses

Chromatic Aberration

Page 17: CPSC 643 Robot Vision

Bahadir K. Gunturk 17

Real Lenses Special lens systems using two or more pieces of glass with

different refractive indeces can reduce or eliminate this problem. However, not even these lens systems are completely perfect and still can lead to visible chromatic aberrations.

Page 18: CPSC 643 Robot Vision

Finite projective camera

1yx

xx

pps

K

C~|IKRP

11 dof (5+3+3)

Page 19: CPSC 643 Robot Vision

Camera Calibration

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Bahadir K. Gunturk 20

Compound Lens Systems

Page 21: CPSC 643 Robot Vision

Lens modelling Thin lens Thick lens Lens with mirrors Radial Distortion

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Real Lenses Barrel Distortion & Pincushion Distortion Stop (Aperture)

Causes of distortion

(normal)

Chief ray

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