Computer VisionComputer Vision

Computer Engineering Sejong UniversityComputer Engineering, Sejong University

Dongil HanDongil Han

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Chapter 1: Cameras

Lens Human Eye Human Eye Image sensorg

Optical Engineering Sejong UniversityOptical Engineering, Sejong UniversityYouSeok Kim

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Lens

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P ti P j ti i h l ti

Lens

Perspective Projection : pinhole perspective

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Lens

P ti P j ti i h l tiPerspective Projection : pinhole perspective

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Lens

P ti P j ti i h l tiPerspective Projection : pinhole perspective

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Affi P j ti k ti

Lens

Affine Projection : weak-perspective

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Lens

Affi P j ti th hi j tiAffine Projection : orthographic projection

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S h i l P j ti

Lens

Spherical Projection

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C ith l

Lens

Camera with lenses

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Lens

C ith l S ll lCamera with lens : Snells law

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Fi t d G t i O ti

Lens

First-order Geometric Optics

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Thi L G t

Lens

Thin Lenses : Geometry

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Thi L G t

Lens

Thin Lenses : Geometry

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Thi L G t

Lens

Thin Lenses : Geometry

Thin lens equation

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D th f fil d

Lens

Depth of filed

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Fil d f i

Lens

Filed of view

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Lens

Real Lens

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Ab ti

Lens

Aberration

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Ab ti S h i l b ti

Lens

Aberration-Spherical aberration

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Ab ti b ti

Lens

Aberration-coma aberration

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Ab ti A ti ti

Lens

Aberration-Astigmatism

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Ab ti fil d t

Lens

Aberration-filed curvature

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Ab ti Di t ti

Lens

Aberration-Distortion

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Ab ti Ch ti b ti

Lens

Aberration-Chromatic aberration

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Vi tti

Lens

Vignetting

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R l L

Lens

Real Lens

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Human Eye

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Human Eye

Structure of the human eye

Cornea :

Pupil :

Iris :

Lens : Blind

Retina :

Fovea :

Spot

Fovea :

Blind Spot :

O ti N Optic Nerve :

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R d d C

Human Eye

Rods

Rods and Cones

- respond to dim light for BW vision- respond to form and movement- do not contribute color vision

Cones- provide daylight color visionprovide daylight color vision- one of 3 spectral types: S(blue), M(green), L(red)- concentrated in the center of retina

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Human Eye

Human Eye

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h i

Human Eye

The Human Perception

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Human Eye

h d d C i l lThe Rod and Cone signal example

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Human Eye

Image Formation in the Eye

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B i ht Ad t ti

Human Eye

Brightness Adaptation

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B i ht Di i i ti

Human Eye

Brightness Discrimination

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P i d B i ht

Human Eye

Perceived Brightness

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Human Eye

Simultaneous Contrast

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O ti l ill i

Human Eye

Optical illusions

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Human Eye

1. 3 DD /

DD

1. 1. (vergence)2. (binocular disparity)

D

2. 1. (accomodation)

2. (motion parallax)3. (visual field size)4. (aerial perspective)5 (li ti )5. (linear perspective)6. (texture gradient)

3 /Takehiro Izumi /NHK

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3 , /Takehiro Izumi, /NHK , /, (1995)

Image sensor

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I i iti i i l

Image sensor

Image acquisition using a single sensor

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I i iti i li

Image sensor

Image acquisition using a line sensor

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I S i

Image sensor

Image Sensing

I i i Incoming energy is transformed into voltage.

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I i iti i

Image sensor

Image acquisition using a array sensor

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I f ti d l

Image sensor

Image formation model

- Creating a Digital Image

For computer processing, an image intensity function f(x,y) must be digitized both spatially and in amplitude. And f(x,y) must be non-zero and finitefinite.

0 < f(x,y)