SlideShare une entreprise Scribd logo
1  sur  45
Télécharger pour lire hors ligne
Elements of visual perception
Dr T M Inbamalar
Visual Perception
Visual Perception
Human visual system
Structure of the Human Eye
Structure of the Human Eye
• The eye is nearly spherical in form with an
average diameter of approximately 20 mm.
• It is enclosed by three membranes;
the cornea and sclera outer cover, the choroid,
and the retina.
• The cornea is a tough, transparent tissue that
covers the anterior or front surface of the eye.
The sclera is continuous with the cornea.
• It is the opaque membrane that encloses the
remainder of the eye.
Elements of visual perception
• The complex physical process of visualizing
something involves the nearly simultaneous
interaction of the eyes and the brain through a
network of neurons, receptors, and other
specialized cells.
• The human eye is equipped with a variety of
optical elements including the cornea, iris, pupil,
a variable-focus lens, and the retina.
• Together, these elements work to form images of
the objects in a person's field of view.
Human vision
• When an object is observed, it is first focused through the cornea
and lens onto the retina.
• Retina is a multilayered membrane that contains millions of light-
sensitive cells that detect the image and translate it into a series of
electrical signals.
• These image capturing receptors of the retina are
termed rods and cones
• Cones and Rods are connected with the fibers of the optic nerve
bundle through a series of specialized cells that coordinate the
transmission of the electrical signals to the brain.
• In the brain, the optic nerves from both eyes join at the optic
chiasma where information from their retinas is correlated.
• The visual information is then processed through several steps,
eventually arriving at the visual cortex, which is located on the
lower rear section of each half of the cerebrum.
Human vision
• Our eyes take in light waves for our visual cortex to process into a
perception.
• The light passes through the cornea and is focused onto the retina
with the lens.
• The retina then controls the amount of light that enters the eye.
• Rods and cones are used to process color in the light and dark.
• Rods are responsible for processing images in a dark atmosphere.
• They are more sensitive and account for peripheral vision.
• The cones are prominent in daylight.
• The optic nerve primarily routes information to the cerebral cortex,
where visual perception occurs.
Human vision
• A particularly specialized component of the eye is the fovea
centralis, which is located on the optical axis of the eye in an area
near the center of the retina.
• This area exclusively contains high-density tightly packed cone cells
and is the area of sharpest vision.
• The density level of cone cells decreases outside of the fovea
centralis and the ratio of rod cells to cone cells gradually increases.
• At the periphery of the retina, the total number of both types of
light receptors decreases substantially, causing a dramatic loss of
visual sensitivity at the retinal borders.
• This is offset, however, by the fact that humans constantly scan
objects in their field of view, usually resulting in a perceived image
that is uniformly sharp
Human vision
Cones and Rods
Cones and Rods
Cones and Rods
• In the human eye, there are two distinct visual
systems (based on two types of retinal cells)
• Scotopic vision: not color sensitive, more
sensitive to light and mainly peripheral (rods)
• Photopic vision : color sensitive, less sensitive
to light and mainly central (cones)
Image formation in the Eye
1. Representation of an object
2. Light leaves the object - propagating in all
directions
3. Some of the light leaving the object reaches
the eye
4. Light changes direction when it passes from
the air into the eye
5. Location of Focused Image
Image formation in the Eye
Structure of the Eye
Brightness Adaptation and
Discrimination
• The ability of the eye to discriminate between
different brightness levels is an important
consideration in creating and presenting
images.
• The range of light intensity levels to which the
human visual system can adapt is on the
order of 1010 from the scotopic threshold
(minimum low light condition) to the glare
limit (maximum light level condition).
Subjective brightness
• Subjective brightness is brightness as
perceived by the human visual system
• Subjective brightness is a logarithmic function
of the light intensity incident on the eye.
• This characteristic is illustrated in the figure
below, which is a plot of light intensity versus
subjective brightness.
Brightness adaptation
• The long solid curve represents the range of
intensities to which the visual system can adapt.
• In photopic vision alone, the range is about 106.
• The transition from scotopic to photopic vision is
gradual over the approximate range from 0.001
to 0.1 millilambert (-3 to -1 mL in the log scale),
as illustrated by the double branches of the
adaptation curve in this range.
Brightness adaptation
• For a given set of conditions, the current sensitivity level of
the visual system is called the brightness-adaptation level
which may correspond, for example, to brightness Ba in the
figure.
• The short intersecting curve represents the range of
subjective brightness that the eye can perceive when
adapted to this level. This range is rather restricted, having
a level Bb at and below which all stimuli are perceived as
indistinguishable blacks.
• The upper (dashed) portion of the curve is not actually
restricted but, if extended too far, loses its meaning
because much higher intensities would simply raise the
adaptation level to a higher value than Ba.
Brightness adaptation
• The visual system cannot operate over such a
range simultaneously. It accomplishes this large
variation by changes in its overall sensitivity. This
phenomenon is known as brightness adaptation.
• The total range of intensity levels it can
discriminate simultaneously is rather small
compared with the total range.
• For any given set of conditions, the current
sensitivity level of the visual system is called
the brightness adaptation level.
Brightness adaptation
• Two phenomena clearly demonstrate that
perceived brightness is not a simple function
of intensity:
• Mach Bands
• simultaneous contrast
Mach Bands
Mach Bands
• The Mach bands effect is due to the spatial
high-boost filtering performed by the human
visual system on the luminance channel of the
image captured by the retina.
• Along the boundary between adjacent
shades of grey in the Mach bands illusion,
lateral inhibition makes the darker area falsely
appear even darker and the lighter area
falsely appear even lighter.
Mach Bands
• In the case of visual information, such (spatial)
differentiation causes gradual changes in the contrast
between an object and its background to be enhanced,
i.e., to become more visible.
• In human perception, this contrast enhancement
produces what is known as Mach Bands: between two
regions of different intensity a thin bright band appears
at the lighter side and a thin dark band appears on the
darker size.
• These bands are not physically present are "overshoot"
and "undershoot" caused by our neural circuits in
processing a step discontinuity in illumination.
Simultaneous Contrast
• The simultaneous contrast phenomenon: each
small square is actually the same intensity but,
because of the different intensities of the
surrounds, the small squares do not appear
equally bright.
• The hue of a patch is also dependent on the
wavelength composition of surrounding light.
• A white patch on a black background will appear
to be yellowish if the surround is a blue light.
Simultaneous Contrast
Optical illusion
• An optical illusion (also called a visual illusion
is an illusion caused by the visual system and
characterized by a visual percept that appears
to differ from reality.
• The eye fills in non-existing information or
wrongly perceives geometrical properties of
objects
Optical illusion

Contenu connexe

Tendances

Edge linking in image processing
Edge linking in image processingEdge linking in image processing
Edge linking in image processingVARUN KUMAR
 
Chapter 3 image enhancement (spatial domain)
Chapter 3 image enhancement (spatial domain)Chapter 3 image enhancement (spatial domain)
Chapter 3 image enhancement (spatial domain)asodariyabhavesh
 
Chapter 2 Image Processing: Pixel Relation
Chapter 2 Image Processing: Pixel RelationChapter 2 Image Processing: Pixel Relation
Chapter 2 Image Processing: Pixel RelationVarun Ojha
 
Image Enhancement in Spatial Domain
Image Enhancement in Spatial DomainImage Enhancement in Spatial Domain
Image Enhancement in Spatial DomainA B Shinde
 
Image segmentation ppt
Image segmentation pptImage segmentation ppt
Image segmentation pptGichelle Amon
 
Histogram Processing
Histogram ProcessingHistogram Processing
Histogram ProcessingAmnaakhaan
 
Image processing presentataion
Image processing presentataionImage processing presentataion
Image processing presentataionRafi Ullah
 
Lecture 4 Relationship between pixels
Lecture 4 Relationship between pixelsLecture 4 Relationship between pixels
Lecture 4 Relationship between pixelsVARUN KUMAR
 
Fundamentals steps in Digital Image processing
Fundamentals steps in Digital Image processingFundamentals steps in Digital Image processing
Fundamentals steps in Digital Image processingKarthicaMarasamy
 
Image Enhancement - Point Processing
Image Enhancement - Point ProcessingImage Enhancement - Point Processing
Image Enhancement - Point ProcessingGayathri31093
 
Chapter10 image segmentation
Chapter10 image segmentationChapter10 image segmentation
Chapter10 image segmentationasodariyabhavesh
 
HSI MODEL IN COLOR IMAGE PROCESSING
HSI MODEL IN COLOR IMAGE PROCESSING HSI MODEL IN COLOR IMAGE PROCESSING
HSI MODEL IN COLOR IMAGE PROCESSING anam singla
 
Image Enhancement using Frequency Domain Filters
Image Enhancement using Frequency Domain FiltersImage Enhancement using Frequency Domain Filters
Image Enhancement using Frequency Domain FiltersKarthika Ramachandran
 
Digital image processing
Digital image processingDigital image processing
Digital image processingABIRAMI M
 
digital image processing
digital image processingdigital image processing
digital image processingAbinaya B
 
Watershed Segmentation Image Processing
Watershed Segmentation Image ProcessingWatershed Segmentation Image Processing
Watershed Segmentation Image ProcessingArshad Hussain
 

Tendances (20)

Edge linking in image processing
Edge linking in image processingEdge linking in image processing
Edge linking in image processing
 
Chapter 3 image enhancement (spatial domain)
Chapter 3 image enhancement (spatial domain)Chapter 3 image enhancement (spatial domain)
Chapter 3 image enhancement (spatial domain)
 
Chapter 2 Image Processing: Pixel Relation
Chapter 2 Image Processing: Pixel RelationChapter 2 Image Processing: Pixel Relation
Chapter 2 Image Processing: Pixel Relation
 
Image Enhancement in Spatial Domain
Image Enhancement in Spatial DomainImage Enhancement in Spatial Domain
Image Enhancement in Spatial Domain
 
Image segmentation ppt
Image segmentation pptImage segmentation ppt
Image segmentation ppt
 
Image enhancement
Image enhancementImage enhancement
Image enhancement
 
Histogram Processing
Histogram ProcessingHistogram Processing
Histogram Processing
 
Image processing presentataion
Image processing presentataionImage processing presentataion
Image processing presentataion
 
Lecture 4 Relationship between pixels
Lecture 4 Relationship between pixelsLecture 4 Relationship between pixels
Lecture 4 Relationship between pixels
 
Fundamentals steps in Digital Image processing
Fundamentals steps in Digital Image processingFundamentals steps in Digital Image processing
Fundamentals steps in Digital Image processing
 
Image Enhancement - Point Processing
Image Enhancement - Point ProcessingImage Enhancement - Point Processing
Image Enhancement - Point Processing
 
Chapter10 image segmentation
Chapter10 image segmentationChapter10 image segmentation
Chapter10 image segmentation
 
Digital Image Processing
Digital Image ProcessingDigital Image Processing
Digital Image Processing
 
image compression ppt
image compression pptimage compression ppt
image compression ppt
 
HSI MODEL IN COLOR IMAGE PROCESSING
HSI MODEL IN COLOR IMAGE PROCESSING HSI MODEL IN COLOR IMAGE PROCESSING
HSI MODEL IN COLOR IMAGE PROCESSING
 
Image Enhancement using Frequency Domain Filters
Image Enhancement using Frequency Domain FiltersImage Enhancement using Frequency Domain Filters
Image Enhancement using Frequency Domain Filters
 
Digital image processing
Digital image processingDigital image processing
Digital image processing
 
digital image processing
digital image processingdigital image processing
digital image processing
 
Wiener Filter
Wiener FilterWiener Filter
Wiener Filter
 
Watershed Segmentation Image Processing
Watershed Segmentation Image ProcessingWatershed Segmentation Image Processing
Watershed Segmentation Image Processing
 

Similaire à Elements of visual perception

Similaire à Elements of visual perception (20)

Elements of visual perception Eye vision .pptx
Elements of visual perception Eye  vision .pptxElements of visual perception Eye  vision .pptx
Elements of visual perception Eye vision .pptx
 
Opticsandphotoactivation
OpticsandphotoactivationOpticsandphotoactivation
Opticsandphotoactivation
 
Dip 1.2 12
Dip 1.2 12Dip 1.2 12
Dip 1.2 12
 
eye.pptx
eye.pptxeye.pptx
eye.pptx
 
PHSIO OF VISION in Ophthalmology in detail
PHSIO OF VISION in Ophthalmology in detailPHSIO OF VISION in Ophthalmology in detail
PHSIO OF VISION in Ophthalmology in detail
 
Physiology of sight and the eye
Physiology of sight and the eyePhysiology of sight and the eye
Physiology of sight and the eye
 
PHYSIOLOGY OF VISION,Part -II
PHYSIOLOGY OF VISION,Part -IIPHYSIOLOGY OF VISION,Part -II
PHYSIOLOGY OF VISION,Part -II
 
Vision1
Vision1Vision1
Vision1
 
Retina & the vision
Retina & the visionRetina & the vision
Retina & the vision
 
Binocular vision
Binocular visionBinocular vision
Binocular vision
 
06 lec9
06 lec906 lec9
06 lec9
 
EYE PRESENTATION Dr Sheeba.ppt
EYE PRESENTATION   Dr Sheeba.pptEYE PRESENTATION   Dr Sheeba.ppt
EYE PRESENTATION Dr Sheeba.ppt
 
Lect 02 first portion
Lect 02   first portionLect 02   first portion
Lect 02 first portion
 
Lect 02 first portion
Lect 02   first portionLect 02   first portion
Lect 02 first portion
 
Confocal microscopy dinesh
Confocal microscopy dineshConfocal microscopy dinesh
Confocal microscopy dinesh
 
Anatomy and physilogy of eye,nose and throat
Anatomy and physilogy of eye,nose and throatAnatomy and physilogy of eye,nose and throat
Anatomy and physilogy of eye,nose and throat
 
Physiolology of Eye: Power of Accommodation and Perimetry
Physiolology of Eye: Power of Accommodation and PerimetryPhysiolology of Eye: Power of Accommodation and Perimetry
Physiolology of Eye: Power of Accommodation and Perimetry
 
CGch-3.pptx
CGch-3.pptxCGch-3.pptx
CGch-3.pptx
 
MICROSCOPY.pdf
MICROSCOPY.pdfMICROSCOPY.pdf
MICROSCOPY.pdf
 
Physiology of sight
Physiology of sightPhysiology of sight
Physiology of sight
 

Plus de Dr INBAMALAR T M

Plus de Dr INBAMALAR T M (8)

Biopotential electrodes
Biopotential electrodesBiopotential electrodes
Biopotential electrodes
 
Biopotential
BiopotentialBiopotential
Biopotential
 
Image color models
Image color modelsImage color models
Image color models
 
Research and Publications
Research and PublicationsResearch and Publications
Research and Publications
 
Intellectual Property Rights
Intellectual Property RightsIntellectual Property Rights
Intellectual Property Rights
 
Counseling
Counseling Counseling
Counseling
 
Outcome based Education
Outcome based EducationOutcome based Education
Outcome based Education
 
Power point quiz crazy quiz template
Power point quiz crazy quiz templatePower point quiz crazy quiz template
Power point quiz crazy quiz template
 

Dernier

Call Girls Narol 7397865700 Independent Call Girls
Call Girls Narol 7397865700 Independent Call GirlsCall Girls Narol 7397865700 Independent Call Girls
Call Girls Narol 7397865700 Independent Call Girlsssuser7cb4ff
 
Concrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptxConcrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptxKartikeyaDwivedi3
 
UNIT III ANALOG ELECTRONICS (BASIC ELECTRONICS)
UNIT III ANALOG ELECTRONICS (BASIC ELECTRONICS)UNIT III ANALOG ELECTRONICS (BASIC ELECTRONICS)
UNIT III ANALOG ELECTRONICS (BASIC ELECTRONICS)Dr SOUNDIRARAJ N
 
Work Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvvWork Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvvLewisJB
 
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfCCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfAsst.prof M.Gokilavani
 
TechTAC® CFD Report Summary: A Comparison of Two Types of Tubing Anchor Catchers
TechTAC® CFD Report Summary: A Comparison of Two Types of Tubing Anchor CatchersTechTAC® CFD Report Summary: A Comparison of Two Types of Tubing Anchor Catchers
TechTAC® CFD Report Summary: A Comparison of Two Types of Tubing Anchor Catcherssdickerson1
 
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionSachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionDr.Costas Sachpazis
 
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)dollysharma2066
 
An experimental study in using natural admixture as an alternative for chemic...
An experimental study in using natural admixture as an alternative for chemic...An experimental study in using natural admixture as an alternative for chemic...
An experimental study in using natural admixture as an alternative for chemic...Chandu841456
 
Piping Basic stress analysis by engineering
Piping Basic stress analysis by engineeringPiping Basic stress analysis by engineering
Piping Basic stress analysis by engineeringJuanCarlosMorales19600
 
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort serviceGurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort servicejennyeacort
 
Unit7-DC_Motors nkkjnsdkfnfcdfknfdgfggfg
Unit7-DC_Motors nkkjnsdkfnfcdfknfdgfggfgUnit7-DC_Motors nkkjnsdkfnfcdfknfdgfggfg
Unit7-DC_Motors nkkjnsdkfnfcdfknfdgfggfgsaravananr517913
 
Past, Present and Future of Generative AI
Past, Present and Future of Generative AIPast, Present and Future of Generative AI
Past, Present and Future of Generative AIabhishek36461
 
US Department of Education FAFSA Week of Action
US Department of Education FAFSA Week of ActionUS Department of Education FAFSA Week of Action
US Department of Education FAFSA Week of ActionMebane Rash
 
Class 1 | NFPA 72 | Overview Fire Alarm System
Class 1 | NFPA 72 | Overview Fire Alarm SystemClass 1 | NFPA 72 | Overview Fire Alarm System
Class 1 | NFPA 72 | Overview Fire Alarm Systemirfanmechengr
 
IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024Mark Billinghurst
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024hassan khalil
 
Instrumentation, measurement and control of bio process parameters ( Temperat...
Instrumentation, measurement and control of bio process parameters ( Temperat...Instrumentation, measurement and control of bio process parameters ( Temperat...
Instrumentation, measurement and control of bio process parameters ( Temperat...121011101441
 

Dernier (20)

Call Girls Narol 7397865700 Independent Call Girls
Call Girls Narol 7397865700 Independent Call GirlsCall Girls Narol 7397865700 Independent Call Girls
Call Girls Narol 7397865700 Independent Call Girls
 
Concrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptxConcrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptx
 
UNIT III ANALOG ELECTRONICS (BASIC ELECTRONICS)
UNIT III ANALOG ELECTRONICS (BASIC ELECTRONICS)UNIT III ANALOG ELECTRONICS (BASIC ELECTRONICS)
UNIT III ANALOG ELECTRONICS (BASIC ELECTRONICS)
 
Design and analysis of solar grass cutter.pdf
Design and analysis of solar grass cutter.pdfDesign and analysis of solar grass cutter.pdf
Design and analysis of solar grass cutter.pdf
 
Work Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvvWork Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvv
 
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfCCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
 
TechTAC® CFD Report Summary: A Comparison of Two Types of Tubing Anchor Catchers
TechTAC® CFD Report Summary: A Comparison of Two Types of Tubing Anchor CatchersTechTAC® CFD Report Summary: A Comparison of Two Types of Tubing Anchor Catchers
TechTAC® CFD Report Summary: A Comparison of Two Types of Tubing Anchor Catchers
 
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionSachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
 
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)
Call Us ≽ 8377877756 ≼ Call Girls In Shastri Nagar (Delhi)
 
An experimental study in using natural admixture as an alternative for chemic...
An experimental study in using natural admixture as an alternative for chemic...An experimental study in using natural admixture as an alternative for chemic...
An experimental study in using natural admixture as an alternative for chemic...
 
Piping Basic stress analysis by engineering
Piping Basic stress analysis by engineeringPiping Basic stress analysis by engineering
Piping Basic stress analysis by engineering
 
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort serviceGurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
 
Unit7-DC_Motors nkkjnsdkfnfcdfknfdgfggfg
Unit7-DC_Motors nkkjnsdkfnfcdfknfdgfggfgUnit7-DC_Motors nkkjnsdkfnfcdfknfdgfggfg
Unit7-DC_Motors nkkjnsdkfnfcdfknfdgfggfg
 
Past, Present and Future of Generative AI
Past, Present and Future of Generative AIPast, Present and Future of Generative AI
Past, Present and Future of Generative AI
 
young call girls in Green Park🔝 9953056974 🔝 escort Service
young call girls in Green Park🔝 9953056974 🔝 escort Serviceyoung call girls in Green Park🔝 9953056974 🔝 escort Service
young call girls in Green Park🔝 9953056974 🔝 escort Service
 
US Department of Education FAFSA Week of Action
US Department of Education FAFSA Week of ActionUS Department of Education FAFSA Week of Action
US Department of Education FAFSA Week of Action
 
Class 1 | NFPA 72 | Overview Fire Alarm System
Class 1 | NFPA 72 | Overview Fire Alarm SystemClass 1 | NFPA 72 | Overview Fire Alarm System
Class 1 | NFPA 72 | Overview Fire Alarm System
 
IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024
 
Instrumentation, measurement and control of bio process parameters ( Temperat...
Instrumentation, measurement and control of bio process parameters ( Temperat...Instrumentation, measurement and control of bio process parameters ( Temperat...
Instrumentation, measurement and control of bio process parameters ( Temperat...
 

Elements of visual perception

  • 1. Elements of visual perception Dr T M Inbamalar
  • 5.
  • 6.
  • 7. Structure of the Human Eye
  • 8. Structure of the Human Eye • The eye is nearly spherical in form with an average diameter of approximately 20 mm. • It is enclosed by three membranes; the cornea and sclera outer cover, the choroid, and the retina. • The cornea is a tough, transparent tissue that covers the anterior or front surface of the eye. The sclera is continuous with the cornea. • It is the opaque membrane that encloses the remainder of the eye.
  • 9. Elements of visual perception • The complex physical process of visualizing something involves the nearly simultaneous interaction of the eyes and the brain through a network of neurons, receptors, and other specialized cells. • The human eye is equipped with a variety of optical elements including the cornea, iris, pupil, a variable-focus lens, and the retina. • Together, these elements work to form images of the objects in a person's field of view.
  • 10.
  • 11. Human vision • When an object is observed, it is first focused through the cornea and lens onto the retina. • Retina is a multilayered membrane that contains millions of light- sensitive cells that detect the image and translate it into a series of electrical signals. • These image capturing receptors of the retina are termed rods and cones • Cones and Rods are connected with the fibers of the optic nerve bundle through a series of specialized cells that coordinate the transmission of the electrical signals to the brain. • In the brain, the optic nerves from both eyes join at the optic chiasma where information from their retinas is correlated. • The visual information is then processed through several steps, eventually arriving at the visual cortex, which is located on the lower rear section of each half of the cerebrum.
  • 12. Human vision • Our eyes take in light waves for our visual cortex to process into a perception. • The light passes through the cornea and is focused onto the retina with the lens. • The retina then controls the amount of light that enters the eye. • Rods and cones are used to process color in the light and dark. • Rods are responsible for processing images in a dark atmosphere. • They are more sensitive and account for peripheral vision. • The cones are prominent in daylight. • The optic nerve primarily routes information to the cerebral cortex, where visual perception occurs.
  • 13. Human vision • A particularly specialized component of the eye is the fovea centralis, which is located on the optical axis of the eye in an area near the center of the retina. • This area exclusively contains high-density tightly packed cone cells and is the area of sharpest vision. • The density level of cone cells decreases outside of the fovea centralis and the ratio of rod cells to cone cells gradually increases. • At the periphery of the retina, the total number of both types of light receptors decreases substantially, causing a dramatic loss of visual sensitivity at the retinal borders. • This is offset, however, by the fact that humans constantly scan objects in their field of view, usually resulting in a perceived image that is uniformly sharp
  • 17.
  • 18.
  • 19.
  • 20.
  • 21. Cones and Rods • In the human eye, there are two distinct visual systems (based on two types of retinal cells) • Scotopic vision: not color sensitive, more sensitive to light and mainly peripheral (rods) • Photopic vision : color sensitive, less sensitive to light and mainly central (cones)
  • 22. Image formation in the Eye 1. Representation of an object 2. Light leaves the object - propagating in all directions 3. Some of the light leaving the object reaches the eye 4. Light changes direction when it passes from the air into the eye 5. Location of Focused Image
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30. Brightness Adaptation and Discrimination • The ability of the eye to discriminate between different brightness levels is an important consideration in creating and presenting images. • The range of light intensity levels to which the human visual system can adapt is on the order of 1010 from the scotopic threshold (minimum low light condition) to the glare limit (maximum light level condition).
  • 31. Subjective brightness • Subjective brightness is brightness as perceived by the human visual system • Subjective brightness is a logarithmic function of the light intensity incident on the eye. • This characteristic is illustrated in the figure below, which is a plot of light intensity versus subjective brightness.
  • 32.
  • 33. Brightness adaptation • The long solid curve represents the range of intensities to which the visual system can adapt. • In photopic vision alone, the range is about 106. • The transition from scotopic to photopic vision is gradual over the approximate range from 0.001 to 0.1 millilambert (-3 to -1 mL in the log scale), as illustrated by the double branches of the adaptation curve in this range.
  • 34. Brightness adaptation • For a given set of conditions, the current sensitivity level of the visual system is called the brightness-adaptation level which may correspond, for example, to brightness Ba in the figure. • The short intersecting curve represents the range of subjective brightness that the eye can perceive when adapted to this level. This range is rather restricted, having a level Bb at and below which all stimuli are perceived as indistinguishable blacks. • The upper (dashed) portion of the curve is not actually restricted but, if extended too far, loses its meaning because much higher intensities would simply raise the adaptation level to a higher value than Ba.
  • 35. Brightness adaptation • The visual system cannot operate over such a range simultaneously. It accomplishes this large variation by changes in its overall sensitivity. This phenomenon is known as brightness adaptation. • The total range of intensity levels it can discriminate simultaneously is rather small compared with the total range. • For any given set of conditions, the current sensitivity level of the visual system is called the brightness adaptation level.
  • 36. Brightness adaptation • Two phenomena clearly demonstrate that perceived brightness is not a simple function of intensity: • Mach Bands • simultaneous contrast
  • 38. Mach Bands • The Mach bands effect is due to the spatial high-boost filtering performed by the human visual system on the luminance channel of the image captured by the retina. • Along the boundary between adjacent shades of grey in the Mach bands illusion, lateral inhibition makes the darker area falsely appear even darker and the lighter area falsely appear even lighter.
  • 39. Mach Bands • In the case of visual information, such (spatial) differentiation causes gradual changes in the contrast between an object and its background to be enhanced, i.e., to become more visible. • In human perception, this contrast enhancement produces what is known as Mach Bands: between two regions of different intensity a thin bright band appears at the lighter side and a thin dark band appears on the darker size. • These bands are not physically present are "overshoot" and "undershoot" caused by our neural circuits in processing a step discontinuity in illumination.
  • 40.
  • 41.
  • 42. Simultaneous Contrast • The simultaneous contrast phenomenon: each small square is actually the same intensity but, because of the different intensities of the surrounds, the small squares do not appear equally bright. • The hue of a patch is also dependent on the wavelength composition of surrounding light. • A white patch on a black background will appear to be yellowish if the surround is a blue light.
  • 44. Optical illusion • An optical illusion (also called a visual illusion is an illusion caused by the visual system and characterized by a visual percept that appears to differ from reality. • The eye fills in non-existing information or wrongly perceives geometrical properties of objects