human and computer vision the best vision model we have! knowledge of how images form in the eye can...
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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