Human and Computer Vision

The best vision model we have! Knowledge of how images form in the eye can

help us with processing digital images

We can’t think of image processing without considering the human vision system. We observe and evaluate the images that we process with our visual system.

Without taking this elementary fact into consideration, we may be much misled in the interpretation of images.

Structure of Human Eye

Ciliary muscle

Anterior chamber

CorneaIrisCiliary

bodyLens

Ciliary fibers

Vitreous humor

Visual axis

FoveaBlind spot

Retina

Sclera

Choroid

Nerve & sheath X-section of human eye

The Eye RetinaChoroid

Sclera

FoveaOptic nerve

Aqueoushumor

Cornea

Iris

Eye lens Vitreoushumor

Structure of human eye

Receptorsالمستقبالت - Pattern vision is afforded by the distribution of discrete light receptors over the surface of the retina. Receptors are divided into 2 classes:

Conesمخاريط

Rodsقضبان

Structure of human eye (contd….)

Cones: 6-7 million, located primarily in the central portion of the

retina (the fovea, muscles controlling the eye rotate the eyeball until the image falls on the fovea).

Highly sensitive to color. Each is connected to its own nerve end thus human can

resolve fine details. Cone vision is called photopic or bright-light vision (day

vision). Rods-

75-150 million, distributed over the retina surface. Several rods are connected to a single nerve end reduce the

amount of detail discernible. Serve to give a general, overall picture of the field of view. Sensitive to low levels of illumination. Rod vision is called scotopic or dim-light vision (night

vision).

Rods

Cones Cones

Rods

Blind spot

Num

ber of rods or cones per mm

Temporal on retina NasalPerimetric angle (deg)

Corn sweet

2

CAN and CANNOT

CAN: See black line 1 second of arc on white field. Detect motion to 10 seconds of arc 2 minutes of arc

per second of time. Match brightness or color well (within 2%) (or a few

millimicrons). Process information in parallel.

CAN’T: Judge absolute level or brightness accurately. Determine absolute wavelength of color well. Detect motion faster than 200 per second. See Beyond 0.4 to 0.7 microns.

Image Formation in the Eye

Example: Calculation of retinal image of an object

17100

15 x

mmx 55.2

Test Images

Test Images

•Test images for distances and area estimation:

a) Parallel lines with up to 5% difference in length.

b) Circles with up to 10% difference in radius.

c) The vertical line appears longer but actually has the same length as the horizontal line.

d) Deception by perspective: the upper line appears longer than the lower one but actually have the same length.

Are the purple lines straight or bent?

Do you see gray areas in between the squares? Now where did they come from?

Simultaneous Contrast

All the small squares have exactly the same intensity, but they appear to the eye progressively darker as the background becomes brighter.

Region’s perceived brightness does not depend simply on its intensity.

Which small square is the darkest one ?

An example of simultaneous contrast

Color Perception

Color Representation for images and video How the physical spectra of a scene is transformed into

RGB components, and how these components are transformed to physical spectra at the display

Cones vs. Rods3 types of cones (for color)1 type of rod (night vision, no color) 

Light is a part of EM wave

•Perceived color depends on spectral content (wavelength composition) e.g., 700nm ~ red.•“spectral color” A light with very narrow bandwidth•A light with equal energy in all visible bands appears white.

Illuminating and Reflecting Light

Illuminating sources:المنيره emit light (e.g. the sun, light bulb, TV monitors) perceived color depends on the emitted freq. follows additive rule

» R+G+B=White

Reflecting sources:العاكسه reflect an incoming light (e.g. the color dye, matte

surface, cloth) perceived color depends on reflected freq (=emitted

freq -absorbed freq.) follows subtractive rule

» R+G+B=Black

Reflected Light

The colours that we perceive are determined by the nature of the light reflected from an objectFor example, if white light is shone onto a green object most wavelengths are absorbed, while green light is reflected from the object

White Light

Colours Absorbed

Green Light

Frequency Responses of Cones and the Luminous Efficiency Function

•Absorption spectra Ci( ) has peaks around 450nm (blue), 550nm (green), 620nm (yellow-green) [Jain’s Fig.3.11 (pp61)]

•Color sensation as described by spectral response αi ().

blue

green red

luminance

Color Mixing

Primary colors for illuminating sources: Red, Green, Blue (RGB) Color monitor works by

exciting red, green, blue phosphors using separate electronic guns

Primary colors for reflecting sources (also known as secondary colors): Cyan, Magenta, Yellow (CMY) Color printer works by using

cyan, magenta, yellow and black (CMYK) dyes.

Color complements

Complements on the color circles

Color hue specification

Color Gamut of printing devices

Color Gamut of RGB Monitors

Computer Imaging

Can be defined a acquisition and processing of visual information bycomputer. Computer representation of an image requires the equivalent ofmany thousands of words of data, so the massive amount of data required for image is a primary reason for the development of many sub areas with field of computer imaging, such as image compression and segmentation .Another important aspect of computer imaging involves the ultimate “receiver” of visual information in some cases the human visual system and in others the computer itself.Computer imaging can be separate into two primary categories:

1. Computer Vision.2. Image Processing.

Computer Vision Computer vision computer imaging where the application doses not involve a human being in visual loop. One of the major topics within this field of computer vision is image analysis.

Image ProcessingImage processing is computer imaging where application involves a humanbeing in the visual loop. In other words the image are to be examined and aacted upon by people.The major topics within the field of image processing include:1. Image restoration.استعادة 2. Image enhancement.يعززاويجمل 3. Image compression.

Image Restoration

Is the process of taking an image with some known, or estimateddegradation, and restoring it to its original appearance. Image restoration isoften used in the field of photography or publishing where an image wassomehow degraded but needs to be improved before it can be printed

Involves taking an image and improving it visually, typically by takingadvantages of human Visual Systems responses. One of the simplestenhancement techniques is to simply stretch the contrast of an image.Enhancement methods tend to be problem specific. For example, a methodthat is used to enhance satellite images may not suitable for enhancingmedical images.Although enhancement and restoration are similar in aim, to make an imagelook better. They differ in how they approach the problem. Restorationmethod attempt to model the distortion to the image and reverse thedegradation, where enhancement methods use knowledge of the humanvisual systems responses to improve an image visually.

Image Enhancement

Involves reducing the typically massive amount of data needed torepresent an image. This done by eliminating data that are visuallyunnecessary and by taking advantage of the redundancy that is inherent inmost images. Image processing systems are used in many and various typesof environments, such as:1. Medical community2. Computer – Aided Design3. Virtual Reality4. Image Processing.

Image Compression