SlideShare a Scribd company logo
1 of 49
IMAGE SEGMENTATION
MultiLevel Thresholding
• Powerful cue used by humans to extract objects and
regions.
• Motion arises from
– Objects moving in the scene.
– Relative displacement between the sensing
system and the scene (e.g. robotic applications,
autonomous navigation).
• We will consider motion
– Spatially.
– In the frequency domain.
Use of Motion in Segmentaion
• Difference image and comparison with respect to
a threshold:
ij
1
d (x, y)  
if f (x, y,ti )  f (x, y,tj ) T
0 otherwise
• The images should be registered.
• Illumination should be relatively constant within the
bounds defined by T.
Basic Spatial Motion Segmentation
• Comparison of a reference image with every subsequent
image in the sequence.
• A counter is incremented every time a pixel in the current image
is different from the reference image.
• When the kth frame is being examined, the entry in a given pixel
of the accumulative difference image (ADI) gives the number of
times this pixel differs from its counterpart in the reference
image.
Accumulative Difference Image (ADI)
(x, y) otherwise
• Absolute ADI:
A (x, y) 
Ak1(x, y) 1 if R(x, y)  f (x, y,tk )  T
k 
A k1
• Positive ADI:
if R(x, y)  f (x, y,tk )  T
otherwise(x, y)
P (x, y) 
Pk1(x, y) 1
k P k1
• Negative ADI:
if R(x, y)  f (x, y,tk )  T
otherwise(x, y)
N (x, y) 
Nk 1(x, y) 1
k N k1
• ADIs for a rectangular object moving to southeast.
Absolute Positive Negative
• The nonzero area of the positive ADI gives the size of the object.
• The location of the positive ADI gives the location of the object in the
reference frame.
• The direction and speed may be obtained fom the absolute and
negative ADIs.
• The absolute ADI contains both the positive and negativeADIs.
• To establish a reference image in a non
stationary background.
– Consider the first image as the reference image.
– When a non stationary component has moved out of
its position in the reference frame, the corresponding
background in the current frame may be duplicated
in the reference frame. This is determined by the
positive ADI:
• When the moving object is displaced completely with
respect to the reference frame the positive ADI stops
increasing.
• Subtraction of the car going from left to right to
establish a reference image.
• Repeating the task for all moving objects may result
in a static reference image.
• The method works well only in simple scenarios.

More Related Content

What's hot

Region based segmentation
Region based segmentationRegion based segmentation
Region based segmentationramya marichamy
 
1.arithmetic & logical operations
1.arithmetic & logical operations1.arithmetic & logical operations
1.arithmetic & logical operationsmukesh bhardwaj
 
Digital Image Fundamentals
Digital Image FundamentalsDigital Image Fundamentals
Digital Image FundamentalsA B Shinde
 
Digital Image restoration
Digital Image restorationDigital Image restoration
Digital Image restorationMd Shabir Alam
 
Image segmentation ppt
Image segmentation pptImage segmentation ppt
Image segmentation pptGichelle Amon
 
Thresholding.ppt
Thresholding.pptThresholding.ppt
Thresholding.pptshankar64
 
Edge Detection using Hough Transform
Edge Detection using Hough TransformEdge Detection using Hough Transform
Edge Detection using Hough TransformMrunal Selokar
 
Digital Image Processing - Image Compression
Digital Image Processing - Image CompressionDigital Image Processing - Image Compression
Digital Image Processing - Image CompressionMathankumar S
 
Image Enhancement in Spatial Domain
Image Enhancement in Spatial DomainImage Enhancement in Spatial Domain
Image Enhancement in Spatial DomainDEEPASHRI HK
 
Image Restoration
Image RestorationImage Restoration
Image RestorationPoonam Seth
 
Image Enhancement using Frequency Domain Filters
Image Enhancement using Frequency Domain FiltersImage Enhancement using Frequency Domain Filters
Image Enhancement using Frequency Domain FiltersKarthika Ramachandran
 
Chapter 5 Image Processing: Fourier Transformation
Chapter 5 Image Processing: Fourier TransformationChapter 5 Image Processing: Fourier Transformation
Chapter 5 Image Processing: Fourier TransformationVarun Ojha
 
Image compression in digital image processing
Image compression in digital image processingImage compression in digital image processing
Image compression in digital image processingDHIVYADEVAKI
 
Enhancement in spatial domain
Enhancement in spatial domainEnhancement in spatial domain
Enhancement in spatial domainAshish Kumar
 

What's hot (20)

Region based segmentation
Region based segmentationRegion based segmentation
Region based segmentation
 
image enhancement
 image enhancement image enhancement
image enhancement
 
1.arithmetic & logical operations
1.arithmetic & logical operations1.arithmetic & logical operations
1.arithmetic & logical operations
 
Digital Image Fundamentals
Digital Image FundamentalsDigital Image Fundamentals
Digital Image Fundamentals
 
Digital Image restoration
Digital Image restorationDigital Image restoration
Digital Image restoration
 
Image segmentation ppt
Image segmentation pptImage segmentation ppt
Image segmentation ppt
 
Image segmentation
Image segmentationImage segmentation
Image segmentation
 
Sharpening spatial filters
Sharpening spatial filtersSharpening spatial filters
Sharpening spatial filters
 
Thresholding.ppt
Thresholding.pptThresholding.ppt
Thresholding.ppt
 
Edge Detection using Hough Transform
Edge Detection using Hough TransformEdge Detection using Hough Transform
Edge Detection using Hough Transform
 
Digital Image Processing - Image Compression
Digital Image Processing - Image CompressionDigital Image Processing - Image Compression
Digital Image Processing - Image Compression
 
Mathematical tools in dip
Mathematical tools in dipMathematical tools in dip
Mathematical tools in dip
 
Region based segmentation
Region based segmentationRegion based segmentation
Region based segmentation
 
Image Enhancement in Spatial Domain
Image Enhancement in Spatial DomainImage Enhancement in Spatial Domain
Image Enhancement in Spatial Domain
 
Image Restoration
Image RestorationImage Restoration
Image Restoration
 
Image Enhancement using Frequency Domain Filters
Image Enhancement using Frequency Domain FiltersImage Enhancement using Frequency Domain Filters
Image Enhancement using Frequency Domain Filters
 
Chapter 5 Image Processing: Fourier Transformation
Chapter 5 Image Processing: Fourier TransformationChapter 5 Image Processing: Fourier Transformation
Chapter 5 Image Processing: Fourier Transformation
 
Image compression in digital image processing
Image compression in digital image processingImage compression in digital image processing
Image compression in digital image processing
 
Image compression .
Image compression .Image compression .
Image compression .
 
Enhancement in spatial domain
Enhancement in spatial domainEnhancement in spatial domain
Enhancement in spatial domain
 

Similar to Image segmentation in Digital Image Processing

Visible surface determination
Visible  surface determinationVisible  surface determination
Visible surface determinationPatel Punit
 
3D transformation and viewing
3D transformation and viewing3D transformation and viewing
3D transformation and viewingYogita Jain
 
3D transformation in computer graphics
3D transformation in computer graphics3D transformation in computer graphics
3D transformation in computer graphicsSHIVANI SONI
 
Geometry of Aerial Photographs.pdf
Geometry of Aerial Photographs.pdfGeometry of Aerial Photographs.pdf
Geometry of Aerial Photographs.pdfkunedzimwefrancisca
 
Fisheye Omnidirectional View in Autonomous Driving
Fisheye Omnidirectional View in Autonomous DrivingFisheye Omnidirectional View in Autonomous Driving
Fisheye Omnidirectional View in Autonomous DrivingYu Huang
 
Use of Specularities and Motion in the Extraction of Surface Shape
Use of Specularities and Motion in the Extraction of Surface ShapeUse of Specularities and Motion in the Extraction of Surface Shape
Use of Specularities and Motion in the Extraction of Surface ShapeDamian T. Gordon
 
Image_processing_unit2_SPPU_Syllabus.pptx
Image_processing_unit2_SPPU_Syllabus.pptxImage_processing_unit2_SPPU_Syllabus.pptx
Image_processing_unit2_SPPU_Syllabus.pptxMayuri Narkhede
 
Lecture 08 tilted photograph
Lecture 08  tilted photographLecture 08  tilted photograph
Lecture 08 tilted photographSarhat Adam
 
Machine Learning - Introduction to Convolutional Neural Networks
Machine Learning - Introduction to Convolutional Neural NetworksMachine Learning - Introduction to Convolutional Neural Networks
Machine Learning - Introduction to Convolutional Neural NetworksAndrew Ferlitsch
 
Computer Vision - Stereo Vision
Computer Vision - Stereo VisionComputer Vision - Stereo Vision
Computer Vision - Stereo VisionWael Badawy
 
chapter 4 computervision.pdf IT IS ABOUT COMUTER VISION
chapter 4 computervision.pdf IT IS ABOUT COMUTER VISIONchapter 4 computervision.pdf IT IS ABOUT COMUTER VISION
chapter 4 computervision.pdf IT IS ABOUT COMUTER VISIONshesnasuneer
 
2D- Transformation
2D- Transformation2D- Transformation
2D- Transformationnehrurevathy
 
matdid950092.pdf
matdid950092.pdfmatdid950092.pdf
matdid950092.pdflencho3d
 
Chapter 6 Image Processing: Image Enhancement
Chapter 6 Image Processing: Image EnhancementChapter 6 Image Processing: Image Enhancement
Chapter 6 Image Processing: Image EnhancementVarun Ojha
 
Hidden surface removal algorithm
Hidden surface removal algorithmHidden surface removal algorithm
Hidden surface removal algorithmKKARUNKARTHIK
 
Digital Image Procesing
Digital Image ProcesingDigital Image Procesing
Digital Image Procesingvepiga5005
 

Similar to Image segmentation in Digital Image Processing (20)

Visible surface determination
Visible  surface determinationVisible  surface determination
Visible surface determination
 
3D transformation and viewing
3D transformation and viewing3D transformation and viewing
3D transformation and viewing
 
Computer graphics presentation
Computer graphics presentationComputer graphics presentation
Computer graphics presentation
 
3D transformation in computer graphics
3D transformation in computer graphics3D transformation in computer graphics
3D transformation in computer graphics
 
Virtual reality
Virtual realityVirtual reality
Virtual reality
 
Geometry of Aerial Photographs.pdf
Geometry of Aerial Photographs.pdfGeometry of Aerial Photographs.pdf
Geometry of Aerial Photographs.pdf
 
Image restoration and reconstruction
Image restoration and reconstructionImage restoration and reconstruction
Image restoration and reconstruction
 
Fisheye Omnidirectional View in Autonomous Driving
Fisheye Omnidirectional View in Autonomous DrivingFisheye Omnidirectional View in Autonomous Driving
Fisheye Omnidirectional View in Autonomous Driving
 
Use of Specularities and Motion in the Extraction of Surface Shape
Use of Specularities and Motion in the Extraction of Surface ShapeUse of Specularities and Motion in the Extraction of Surface Shape
Use of Specularities and Motion in the Extraction of Surface Shape
 
Image_processing_unit2_SPPU_Syllabus.pptx
Image_processing_unit2_SPPU_Syllabus.pptxImage_processing_unit2_SPPU_Syllabus.pptx
Image_processing_unit2_SPPU_Syllabus.pptx
 
Lecture 08 tilted photograph
Lecture 08  tilted photographLecture 08  tilted photograph
Lecture 08 tilted photograph
 
Machine Learning - Introduction to Convolutional Neural Networks
Machine Learning - Introduction to Convolutional Neural NetworksMachine Learning - Introduction to Convolutional Neural Networks
Machine Learning - Introduction to Convolutional Neural Networks
 
Computer Vision - Stereo Vision
Computer Vision - Stereo VisionComputer Vision - Stereo Vision
Computer Vision - Stereo Vision
 
IR.pptx
IR.pptxIR.pptx
IR.pptx
 
chapter 4 computervision.pdf IT IS ABOUT COMUTER VISION
chapter 4 computervision.pdf IT IS ABOUT COMUTER VISIONchapter 4 computervision.pdf IT IS ABOUT COMUTER VISION
chapter 4 computervision.pdf IT IS ABOUT COMUTER VISION
 
2D- Transformation
2D- Transformation2D- Transformation
2D- Transformation
 
matdid950092.pdf
matdid950092.pdfmatdid950092.pdf
matdid950092.pdf
 
Chapter 6 Image Processing: Image Enhancement
Chapter 6 Image Processing: Image EnhancementChapter 6 Image Processing: Image Enhancement
Chapter 6 Image Processing: Image Enhancement
 
Hidden surface removal algorithm
Hidden surface removal algorithmHidden surface removal algorithm
Hidden surface removal algorithm
 
Digital Image Procesing
Digital Image ProcesingDigital Image Procesing
Digital Image Procesing
 

More from DHIVYADEVAKI

Computer Networks - DNS
Computer Networks - DNSComputer Networks - DNS
Computer Networks - DNSDHIVYADEVAKI
 
Error detection methods-computer networks
Error detection methods-computer networksError detection methods-computer networks
Error detection methods-computer networksDHIVYADEVAKI
 
Introduction basic schema and SQL QUERIES
Introduction basic schema and SQL QUERIESIntroduction basic schema and SQL QUERIES
Introduction basic schema and SQL QUERIESDHIVYADEVAKI
 
Data preprocessing in Data Mining
Data preprocessing in Data MiningData preprocessing in Data Mining
Data preprocessing in Data MiningDHIVYADEVAKI
 
Apriori algorithm
Apriori algorithm Apriori algorithm
Apriori algorithm DHIVYADEVAKI
 
Types of Load distributing algorithm in Distributed System
Types of Load distributing algorithm in Distributed SystemTypes of Load distributing algorithm in Distributed System
Types of Load distributing algorithm in Distributed SystemDHIVYADEVAKI
 
Deadlock Detection in Distributed Systems
Deadlock Detection in Distributed SystemsDeadlock Detection in Distributed Systems
Deadlock Detection in Distributed SystemsDHIVYADEVAKI
 

More from DHIVYADEVAKI (8)

Computer Networks - DNS
Computer Networks - DNSComputer Networks - DNS
Computer Networks - DNS
 
Error detection methods-computer networks
Error detection methods-computer networksError detection methods-computer networks
Error detection methods-computer networks
 
Introduction basic schema and SQL QUERIES
Introduction basic schema and SQL QUERIESIntroduction basic schema and SQL QUERIES
Introduction basic schema and SQL QUERIES
 
R graphics
R graphicsR graphics
R graphics
 
Data preprocessing in Data Mining
Data preprocessing in Data MiningData preprocessing in Data Mining
Data preprocessing in Data Mining
 
Apriori algorithm
Apriori algorithm Apriori algorithm
Apriori algorithm
 
Types of Load distributing algorithm in Distributed System
Types of Load distributing algorithm in Distributed SystemTypes of Load distributing algorithm in Distributed System
Types of Load distributing algorithm in Distributed System
 
Deadlock Detection in Distributed Systems
Deadlock Detection in Distributed SystemsDeadlock Detection in Distributed Systems
Deadlock Detection in Distributed Systems
 

Recently uploaded

History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptxHistory Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptxsocialsciencegdgrohi
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13Steve Thomason
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxSayali Powar
 
Alper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentAlper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentInMediaRes1
 
Class 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdfClass 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdfakmcokerachita
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdfSoniaTolstoy
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Educationpboyjonauth
 
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Celine George
 
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,Virag Sontakke
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxpboyjonauth
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptxVS Mahajan Coaching Centre
 
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxProudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxthorishapillay1
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxGaneshChakor2
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTiammrhaywood
 
Pharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfPharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfMahmoud M. Sallam
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 

Recently uploaded (20)

History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptxHistory Class XII Ch. 3 Kinship, Caste and Class (1).pptx
History Class XII Ch. 3 Kinship, Caste and Class (1).pptx
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
 
Alper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentAlper Gobel In Media Res Media Component
Alper Gobel In Media Res Media Component
 
Class 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdfClass 11 Legal Studies Ch-1 Concept of State .pdf
Class 11 Legal Studies Ch-1 Concept of State .pdf
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Education
 
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
Incoming and Outgoing Shipments in 1 STEP Using Odoo 17
 
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,भारत-रोम व्यापार.pptx, Indo-Roman Trade,
भारत-रोम व्यापार.pptx, Indo-Roman Trade,
 
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
 
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdfTataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
 
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxProudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptx
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptx
 
9953330565 Low Rate Call Girls In Rohini Delhi NCR
9953330565 Low Rate Call Girls In Rohini  Delhi NCR9953330565 Low Rate Call Girls In Rohini  Delhi NCR
9953330565 Low Rate Call Girls In Rohini Delhi NCR
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
 
Pharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfPharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdf
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 

Image segmentation in Digital Image Processing

  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.
  • 32.
  • 33.
  • 34.
  • 35.
  • 36.
  • 37.
  • 38.
  • 39.
  • 40.
  • 41.
  • 42.
  • 43. • Powerful cue used by humans to extract objects and regions. • Motion arises from – Objects moving in the scene. – Relative displacement between the sensing system and the scene (e.g. robotic applications, autonomous navigation). • We will consider motion – Spatially. – In the frequency domain. Use of Motion in Segmentaion
  • 44. • Difference image and comparison with respect to a threshold: ij 1 d (x, y)   if f (x, y,ti )  f (x, y,tj ) T 0 otherwise • The images should be registered. • Illumination should be relatively constant within the bounds defined by T. Basic Spatial Motion Segmentation
  • 45. • Comparison of a reference image with every subsequent image in the sequence. • A counter is incremented every time a pixel in the current image is different from the reference image. • When the kth frame is being examined, the entry in a given pixel of the accumulative difference image (ADI) gives the number of times this pixel differs from its counterpart in the reference image. Accumulative Difference Image (ADI)
  • 46. (x, y) otherwise • Absolute ADI: A (x, y)  Ak1(x, y) 1 if R(x, y)  f (x, y,tk )  T k  A k1 • Positive ADI: if R(x, y)  f (x, y,tk )  T otherwise(x, y) P (x, y)  Pk1(x, y) 1 k P k1 • Negative ADI: if R(x, y)  f (x, y,tk )  T otherwise(x, y) N (x, y)  Nk 1(x, y) 1 k N k1
  • 47. • ADIs for a rectangular object moving to southeast. Absolute Positive Negative • The nonzero area of the positive ADI gives the size of the object. • The location of the positive ADI gives the location of the object in the reference frame. • The direction and speed may be obtained fom the absolute and negative ADIs. • The absolute ADI contains both the positive and negativeADIs.
  • 48. • To establish a reference image in a non stationary background. – Consider the first image as the reference image. – When a non stationary component has moved out of its position in the reference frame, the corresponding background in the current frame may be duplicated in the reference frame. This is determined by the positive ADI: • When the moving object is displaced completely with respect to the reference frame the positive ADI stops increasing.
  • 49. • Subtraction of the car going from left to right to establish a reference image. • Repeating the task for all moving objects may result in a static reference image. • The method works well only in simple scenarios.