SlideShare a Scribd company logo
UNIT 2
Introduction to
Image Processing
 What is Image Processing ?
 Applications
 Purpose of Image Processing
 Types of Image Processing
 Components of Image Processing
 Future Scope
 Advantages
 Disadvantages
 Image Processing is any form of signal
processing for which our input is an image, such as
photographs or frames of video and our output can
be either an image or a set of characteristics or
parameters related to the image.
Image Processing generally refers to processing of
two dimensional picture and by two dimensional
picture we implies a digital image.
A digital image is an array of real or complex
numbers represented by a finite number of bits.
But now in these days optical and analog image
processing is also possible.
 Face detection
 Feature detection
 Non-photorealistic rendering
 Medical image processing
 Microscope image processing
 Morphological image processing
 Remote sensing
 Automated Sieving Procedures
 Finger print recognization
 Visualization - Observe the objects that
are not visible.
 Image sharpening and restoration - To
create a better image.
 Image retrieval - Seek for the image of
interest.
 Measurement of pattern – Measures
various objects in an image.
 Image Recognition – Distinguish the
objects in an image.
 Analog Image Processing
 Digital Image Processing
 Optical Image Processing
 Image Sensors
 Image Displays
 Image Processing
 Software(OpenCV,Matlab,CIMG)
 Image Processing Hardware
 Memory
 We all are in midst of revolution ignited by
fast development in computer technology and
imaging.
 Against common belief, computers are not
able to match humans in calculation related
to image processing and analysis.
 But with increasing sophistication and power
of the modern computing, computation will
go beyond conventional, Von Neumann
sequential architecture and would
contemplate the optical execution too.
 This one is more accurate than the overlapping
method because it is based upon minutia.
 It is an interactive method for recognizing
fingerprints.
 It is more time consuming as compared to the
former.
 More complex program.
- Structure of the Human Eye
- Image Formation in the Eye
- Brightness Adaptation and Discrimination
Eye characteristics
– nearly spherical
– approximately 20 mm in diameter
– three membranes
• cornea (transparent) & sclera (opaque) outer cover
• choroid contains a network of blood vessels, heavily pigmented to reduce amount
of extraneous light entering the eye. Also contains the iris diaphragm (2-8 mm to
allow variable amount of light into the eye)
• retina is the inner most membrane, objects are imaged on the surface.
Retinal surface is covered in discrete light receptors
Two classes
– Cones
• 6-7 million located primarily near the center of the retina (the fovea)
• highly sensitive to color
• can resolve fine details because each is attached to a single nerve ending
• Cone vision is called photopic or bright-light vision
– Rods
• 75-150 million distributed over the retinal surface
• multiple rods connected to a single nerve ending
• give a general overall picture of the field of illumination
• not color sensitive but are sensitive to low levels of illumination
• Rod vision is called scotopic or dim-light vision
Rods are thin cells with slender rodlike projections that are the photoreceptors
for:
Black and white vision
Vision in dim light
Cones are the receptors for:
Color vision
Visual acuity
There are three types of cones, each with a different visual pigment
One sensitive to green light
One sensitive to blue light
One sensitive to red light
The perceived color of an object depends on the quantity and combination of
cones that are stimulated
In very dim light, cones do not function
Color blindness occurs because there is an absence or deficiency of one or
more of the visual pigments in the cones. So the person cannot distinguish
certain colors.
What is Image Processing.  Image Process
Pupil allows varying
amounts of light to
enter the eye.
Cornea is a transparent structure that
covers the iris and pupil
Cones are
concentrated in
the center of the
retina - the fovea
Lens helps to focus
light on the retina.
Retina includes
- Rods (94%)
(light sensitive)
- Cones (6%)
(color sensitive)
•Fovea size is 1.5 mm in diameter
•1.5 mm  1.5 mm square contain 337000 cones
5mm  5mm CCD imaging chip
CONT’D…
2.1- Elements of
Visual Perception
2.2- Light and the
Electromagnetic
Spectrum
2.3- Image Sensing
and Acquisition
2.4- Image Sampling
and Quantization
2.5- Some Basic
Relationships
Between Pixels
2.6- An Introduction
to the Mathematical
Tools Used in Digital
Image Processing
The principal difference between the lens of the eyee and an
ordinary optical lens is that the former is flexible.
The radius of curvature of the anterior surface of the lens is
greater than the radius of its posterior or surface.
The shape of the lens is controlled by tension in the fibers of
the ciliary body.
To focus on distant objects, the controlling muscles cause
the lens to be relatively flattened.
Similarly, these muscles allow the lens to become thicker in
order to focus on objects near the eye.
The distance between the center of the lens and the retina
(called the focal length) varies from approximately 17mm to
about 14mm, as the refractive power of the lens increases
from its minimum to its maximum.
When the eye focuses on an object farther away than about
3m, the lens exhibits its lowest refractive power.
When the eye focuses on a nearby object, the lens is most
strongly refractive.
This information makes it easy to calculate the size of the
retinal image of any objects.
Draw an image similar to that below on a piece of
paper (the dot and cross are about 6 inches apart)
Close your right eye and focus on the cross with your
left eye
Hold the image about 20 inches away from your face
and move it slowly towards you
The dot should disappear!
Blind-Spot Experiment
What is Image Processing.  Image Process
Example:
Calculation of retinal image of an object
15/100=h/17 or h=2.55 mm
- Muscles within the eye can be used to change the shape of
the lens allowing us focus on objects that are near or far away
- An image is focused onto the retina causing rods and cones
to become excited which ultimately send signals to the brain
Light receptor
radiant
energy
electrical
impulses
Brain
Range of light intensity levels to which HVS (human
visual system) can adapt: on the order of 1010 _ from the
scotopic threshold to the glare limit.
Subjective brightness (i.e. intensity as perceived by the
HVS) is a logarithmic function of the light intensity
incident on the eye.
• The visual system does not operate
simultaneously over the 1010 range. It
accomplishes this large variation by changes in
its overall sensitivity, a phenomenon known as
brightness adaptation.
For any given set of conditions, the current sensitivity
level of HVS is called the brightness adaptation level.
mL = millilambert
• Brightness discrimination is the ability of the eye to
discriminate between changes in light intensity at any
specific adaptation level.
• The quantity Ic/I, where Ic is the increment of illumination
discriminable 50% of the time with background illumination
I, is called the Weber ratio. A small value of Weber ratio,
means good brightness discrimination.
The eye also discriminates between changes in brightness at any specific
adaptation level.
ratio
Weber


I
Ic
Where: ∆𝐼𝑐: the increment of illumination discriminable 50% of the time
I : background illumination
Typical Weber ratio
as a function of
intensity
CONT’D
Weber ratio (the experiment) Ic/I
I: the background illumination
Ic : the increment of illumination
Small Weber ratio indicates good discrimination
Larger Weber ratio indicates poor discrimination
• Brightness discrimination is poor at low levels of illumination. The
two branches in the curve indicate that at low levels of illumination
vision is carried out by the rods, whereas at high level by the
cones.
Thanks

More Related Content

PPT
Lecture_4_Human_eye_Digital_Image_Processing.ppt
PPTX
Elements of Visual Perceptions Structure
PPTX
Lect 02 first portion
PPTX
Lect 02 first portion
PPTX
Elements of visual perception Eye vision .pptx
PPT
A representation of the original image by a discrete set of data points
PPT
Visionbf 1h-fin
PPTX
Introduction to Elements of Digital image processing
Lecture_4_Human_eye_Digital_Image_Processing.ppt
Elements of Visual Perceptions Structure
Lect 02 first portion
Lect 02 first portion
Elements of visual perception Eye vision .pptx
A representation of the original image by a discrete set of data points
Visionbf 1h-fin
Introduction to Elements of Digital image processing

Similar to What is Image Processing. Image Process (20)

PDF
Eye as an optical system.
PPTX
ch-1.2 elements of visualperception.pptx
PPTX
Blindness and Assistive Systems for Blind Navigation
PDF
Elements of visual perception
PPT
Image processing presentataion
PDF
Dip 4 ece-1 & 2
PPTX
Elements of Visual Perception in digital image processing
PPTX
zfsdaegvazeg.pptx human eye ihsajkfhkja hsfhsjfn
PPTX
94955904-HUMAN-EYE-PRESENTATION.pptx human eye
PPT
Intro_to_Visual Inspection.ppt
PDF
human eye_merged (1) (1).pdf. TOTAL HUMAN EYE AND COLORFUL WORLD CHAPTER.
PPTX
0HY5M94d7TShdydhnsuamalakga न्सकाकाfF8K5372.pptx
PPTX
Human color vision
PPT
chapter 3 - Sensation and perception 2013
PPT
DIGITAL IMAGE FUNDAS.ppt
DOCX
different types of Microscopy..... .docx
PDF
6. 6.6.2020-physiology-EYE__.ppt- Dr Math.pptx.pdf
PPTX
PHYSIOLOGY OF EYE.pptx
PPT
digital image processing cresent ppt slides
PDF
MICROSCOPY.pdf
Eye as an optical system.
ch-1.2 elements of visualperception.pptx
Blindness and Assistive Systems for Blind Navigation
Elements of visual perception
Image processing presentataion
Dip 4 ece-1 & 2
Elements of Visual Perception in digital image processing
zfsdaegvazeg.pptx human eye ihsajkfhkja hsfhsjfn
94955904-HUMAN-EYE-PRESENTATION.pptx human eye
Intro_to_Visual Inspection.ppt
human eye_merged (1) (1).pdf. TOTAL HUMAN EYE AND COLORFUL WORLD CHAPTER.
0HY5M94d7TShdydhnsuamalakga न्सकाकाfF8K5372.pptx
Human color vision
chapter 3 - Sensation and perception 2013
DIGITAL IMAGE FUNDAS.ppt
different types of Microscopy..... .docx
6. 6.6.2020-physiology-EYE__.ppt- Dr Math.pptx.pdf
PHYSIOLOGY OF EYE.pptx
digital image processing cresent ppt slides
MICROSCOPY.pdf
Ad

More from Harmanjot5678 (6)

PPTX
Penetration Testing Using Open Source Technologies.pptx
PPTX
Early Binding, Late Binding, Virtual Fun
PPT
Image Formation Fundamentals Image forma
PPTX
429cf300-0dc7-4c2e-9280-d918d69e3cb4.pptx
PPTX
429cf300-0dc7-4c2e-9280-d918d69e3cb4.pptx
PPTX
429cf300-0dc7-4c2e-9280-d918d69e3cb4.pptx
Penetration Testing Using Open Source Technologies.pptx
Early Binding, Late Binding, Virtual Fun
Image Formation Fundamentals Image forma
429cf300-0dc7-4c2e-9280-d918d69e3cb4.pptx
429cf300-0dc7-4c2e-9280-d918d69e3cb4.pptx
429cf300-0dc7-4c2e-9280-d918d69e3cb4.pptx
Ad

Recently uploaded (20)

DOCX
ASol_English-Language-Literature-Set-1-27-02-2023-converted.docx
PDF
Mitigating Risks through Effective Management for Enhancing Organizational Pe...
PPTX
Lecture Notes Electrical Wiring System Components
PDF
Well-logging-methods_new................
PDF
TFEC-4-2020-Design-Guide-for-Timber-Roof-Trusses.pdf
PPTX
UNIT 4 Total Quality Management .pptx
PDF
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
PPTX
Sustainable Sites - Green Building Construction
PDF
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
DOCX
573137875-Attendance-Management-System-original
PPTX
CH1 Production IntroductoryConcepts.pptx
PDF
Digital Logic Computer Design lecture notes
PPTX
Construction Project Organization Group 2.pptx
PDF
composite construction of structures.pdf
PDF
Embodied AI: Ushering in the Next Era of Intelligent Systems
PDF
Evaluating the Democratization of the Turkish Armed Forces from a Normative P...
PPTX
additive manufacturing of ss316l using mig welding
PPTX
Foundation to blockchain - A guide to Blockchain Tech
PPTX
Infosys Presentation by1.Riyan Bagwan 2.Samadhan Naiknavare 3.Gaurav Shinde 4...
PDF
Enhancing Cyber Defense Against Zero-Day Attacks using Ensemble Neural Networks
ASol_English-Language-Literature-Set-1-27-02-2023-converted.docx
Mitigating Risks through Effective Management for Enhancing Organizational Pe...
Lecture Notes Electrical Wiring System Components
Well-logging-methods_new................
TFEC-4-2020-Design-Guide-for-Timber-Roof-Trusses.pdf
UNIT 4 Total Quality Management .pptx
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
Sustainable Sites - Green Building Construction
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
573137875-Attendance-Management-System-original
CH1 Production IntroductoryConcepts.pptx
Digital Logic Computer Design lecture notes
Construction Project Organization Group 2.pptx
composite construction of structures.pdf
Embodied AI: Ushering in the Next Era of Intelligent Systems
Evaluating the Democratization of the Turkish Armed Forces from a Normative P...
additive manufacturing of ss316l using mig welding
Foundation to blockchain - A guide to Blockchain Tech
Infosys Presentation by1.Riyan Bagwan 2.Samadhan Naiknavare 3.Gaurav Shinde 4...
Enhancing Cyber Defense Against Zero-Day Attacks using Ensemble Neural Networks

What is Image Processing. Image Process

  • 2.  What is Image Processing ?  Applications  Purpose of Image Processing  Types of Image Processing  Components of Image Processing  Future Scope  Advantages  Disadvantages
  • 3.  Image Processing is any form of signal processing for which our input is an image, such as photographs or frames of video and our output can be either an image or a set of characteristics or parameters related to the image.
  • 4. Image Processing generally refers to processing of two dimensional picture and by two dimensional picture we implies a digital image. A digital image is an array of real or complex numbers represented by a finite number of bits. But now in these days optical and analog image processing is also possible.
  • 5.  Face detection  Feature detection  Non-photorealistic rendering  Medical image processing  Microscope image processing  Morphological image processing  Remote sensing  Automated Sieving Procedures  Finger print recognization
  • 6.  Visualization - Observe the objects that are not visible.  Image sharpening and restoration - To create a better image.  Image retrieval - Seek for the image of interest.  Measurement of pattern – Measures various objects in an image.  Image Recognition – Distinguish the objects in an image.
  • 7.  Analog Image Processing  Digital Image Processing  Optical Image Processing
  • 8.  Image Sensors  Image Displays  Image Processing  Software(OpenCV,Matlab,CIMG)  Image Processing Hardware  Memory
  • 9.  We all are in midst of revolution ignited by fast development in computer technology and imaging.  Against common belief, computers are not able to match humans in calculation related to image processing and analysis.  But with increasing sophistication and power of the modern computing, computation will go beyond conventional, Von Neumann sequential architecture and would contemplate the optical execution too.
  • 10.  This one is more accurate than the overlapping method because it is based upon minutia.  It is an interactive method for recognizing fingerprints.
  • 11.  It is more time consuming as compared to the former.  More complex program.
  • 12. - Structure of the Human Eye - Image Formation in the Eye - Brightness Adaptation and Discrimination
  • 13. Eye characteristics – nearly spherical – approximately 20 mm in diameter – three membranes • cornea (transparent) & sclera (opaque) outer cover • choroid contains a network of blood vessels, heavily pigmented to reduce amount of extraneous light entering the eye. Also contains the iris diaphragm (2-8 mm to allow variable amount of light into the eye) • retina is the inner most membrane, objects are imaged on the surface.
  • 14. Retinal surface is covered in discrete light receptors Two classes – Cones • 6-7 million located primarily near the center of the retina (the fovea) • highly sensitive to color • can resolve fine details because each is attached to a single nerve ending • Cone vision is called photopic or bright-light vision – Rods • 75-150 million distributed over the retinal surface • multiple rods connected to a single nerve ending • give a general overall picture of the field of illumination • not color sensitive but are sensitive to low levels of illumination • Rod vision is called scotopic or dim-light vision
  • 15. Rods are thin cells with slender rodlike projections that are the photoreceptors for: Black and white vision Vision in dim light Cones are the receptors for: Color vision Visual acuity There are three types of cones, each with a different visual pigment One sensitive to green light One sensitive to blue light One sensitive to red light The perceived color of an object depends on the quantity and combination of cones that are stimulated In very dim light, cones do not function Color blindness occurs because there is an absence or deficiency of one or more of the visual pigments in the cones. So the person cannot distinguish certain colors.
  • 17. Pupil allows varying amounts of light to enter the eye. Cornea is a transparent structure that covers the iris and pupil Cones are concentrated in the center of the retina - the fovea Lens helps to focus light on the retina. Retina includes - Rods (94%) (light sensitive) - Cones (6%) (color sensitive)
  • 18. •Fovea size is 1.5 mm in diameter •1.5 mm  1.5 mm square contain 337000 cones 5mm  5mm CCD imaging chip CONT’D…
  • 19. 2.1- Elements of Visual Perception 2.2- Light and the Electromagnetic Spectrum 2.3- Image Sensing and Acquisition 2.4- Image Sampling and Quantization 2.5- Some Basic Relationships Between Pixels 2.6- An Introduction to the Mathematical Tools Used in Digital Image Processing The principal difference between the lens of the eyee and an ordinary optical lens is that the former is flexible. The radius of curvature of the anterior surface of the lens is greater than the radius of its posterior or surface. The shape of the lens is controlled by tension in the fibers of the ciliary body. To focus on distant objects, the controlling muscles cause the lens to be relatively flattened. Similarly, these muscles allow the lens to become thicker in order to focus on objects near the eye. The distance between the center of the lens and the retina (called the focal length) varies from approximately 17mm to about 14mm, as the refractive power of the lens increases from its minimum to its maximum. When the eye focuses on an object farther away than about 3m, the lens exhibits its lowest refractive power. When the eye focuses on a nearby object, the lens is most strongly refractive. This information makes it easy to calculate the size of the retinal image of any objects.
  • 20. Draw an image similar to that below on a piece of paper (the dot and cross are about 6 inches apart) Close your right eye and focus on the cross with your left eye Hold the image about 20 inches away from your face and move it slowly towards you The dot should disappear! Blind-Spot Experiment
  • 22. Example: Calculation of retinal image of an object 15/100=h/17 or h=2.55 mm - Muscles within the eye can be used to change the shape of the lens allowing us focus on objects that are near or far away - An image is focused onto the retina causing rods and cones to become excited which ultimately send signals to the brain Light receptor radiant energy electrical impulses Brain
  • 23. Range of light intensity levels to which HVS (human visual system) can adapt: on the order of 1010 _ from the scotopic threshold to the glare limit. Subjective brightness (i.e. intensity as perceived by the HVS) is a logarithmic function of the light intensity incident on the eye. • The visual system does not operate simultaneously over the 1010 range. It accomplishes this large variation by changes in its overall sensitivity, a phenomenon known as brightness adaptation. For any given set of conditions, the current sensitivity level of HVS is called the brightness adaptation level. mL = millilambert
  • 24. • Brightness discrimination is the ability of the eye to discriminate between changes in light intensity at any specific adaptation level. • The quantity Ic/I, where Ic is the increment of illumination discriminable 50% of the time with background illumination I, is called the Weber ratio. A small value of Weber ratio, means good brightness discrimination. The eye also discriminates between changes in brightness at any specific adaptation level. ratio Weber   I Ic Where: ∆𝐼𝑐: the increment of illumination discriminable 50% of the time I : background illumination
  • 25. Typical Weber ratio as a function of intensity CONT’D Weber ratio (the experiment) Ic/I I: the background illumination Ic : the increment of illumination Small Weber ratio indicates good discrimination Larger Weber ratio indicates poor discrimination • Brightness discrimination is poor at low levels of illumination. The two branches in the curve indicate that at low levels of illumination vision is carried out by the rods, whereas at high level by the cones.