CS-803 (A) · Image Processing and Computer Vision/Official Syllabus
Image Processing and Computer Vision (CS-803 (A)) - Official Syllabus
1
Unit 1
Introduction to computer vision and Image processing (CVIP)
- Basics of CVIP
- History of CVIP
- Evolution of CVIP
- CV Models
- Image Filtering
- Image Representations
- Image Statistics
- Conditioning
- Labeling
- Grouping
- Extracting
- Matching
- Morphological Image Processing: Introduction
- Dilation
- Erosion
- Opening
- Closing
- Hit-or-Miss transformation
- Morphological algorithm operations on binary images
- Morphological algorithm operations on gray-scale images
- Thinning
- Thickening
- Region growing, region shrinking
2
Unit 2
Image Representation and Description
- Representation schemes
- Boundary descriptors
- Region descriptors
- Thresholding
- Segmentation
- Connected component labeling
- Hierarchal segmentation
- Spatial clustering
- Split & merge
- Rule-based Segmentation
- Motion-based segmentation
- Area Extraction: Concepts
- Data-structures
- Edge, Line-Linking
- Hough transform
- Line fitting
- Curve fitting (Least-square fitting)
3
Unit 3
Region Analysis
- Region properties
- External points
- Spatial moments
- Mixed spatial gray-level moments
- Signature properties
- Shape numbers
- Distance relational approach
- Ordered structural matching
- View class matching
- Models database organization
4
Unit 4
Facet Model Recognition
- Labeling lines
- Understanding line drawings
- Classification of shapes by labeling of edges
- Recognition of shapes
- Consisting labeling problem
- Back-tracking Algorithm
- Perspective Projective geometry
- Inverse perspective Projection
- Photogrammetric -from 2D to 3D
- Image matching: Intensity matching of ID signals
- Matching of 2D image
- Hierarchical image matching
- Object Models And Matching: 2D representation
- Global vs. Local features
5
Unit 5
Knowledge Based Vision
- Knowledge representation
- Control-strategies
- Information Integration
- Object recognition-Hough transforms and other simple object recognition methods
- Shape correspondence and shape matching
- Principal component analysis
- feature extraction
- Neural network and Machine learning for image shape recognition
Reference Books
- Computer and Robot Vision — Robert Haralick, Linda Shapiro
- Computer Vision: A Modern Approach — David A. Forsyth, Jean Ponce
- Image Processing, Analysis, and Machine Vision — Milan Sonka, Vaclav Hlavac, Roger Boyle
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