Subject Syllabus
CS-803 (A) - Image Processing and Computer Vision
CSE · Semester 8
Course Modules
Learn topic-wise with Hyper AI and revise using mapped PYQs.
Basics of CVIP, History of CVIP, Evolution of CVIP, CV ModelsImage Filtering, Image Representations, Image StatisticsRecognition Methodology: Conditioning, Labeling, Grouping, Extracting, and MatchingMorphological Image Processing: Introduction, Dilation, Erosion, Opening, Closing, Hit-or-Miss transformationMorphological algorithm operations on binary images, Morphological algorithm operations on gray-scale imagesThinning, Thickening, Region growing, region shrinking
Representation schemes, Boundary descriptors, Region descriptorsBinary Machine Vision: Thresholding, Segmentation, Connected component labelingHierarchal segmentation, Spatial clustering, Split & merge, Rule-based Segmentation, Motion-based segmentationArea Extraction: Concepts, Data-structures, Edge, Line-Linking, Hough transform, Line fitting, Curve fitting (Least-square fitting)
Labeling lines, Understanding line drawingsClassification of shapes by labeling of edges, Recognition of shapesConsisting labeling problem, Back-tracking AlgorithmPerspective Projective geometry, Inverse perspective Projection, Photogrammetric - from 2D to 3DImage matching: Intensity matching of ID signals, Matching of 2D image, Hierarchical image matchingObject Models And Matching: 2D representation, Global vs. Local features
Knowledge representation, Control-strategies, Information IntegrationObject recognition - Hough transforms and other simple object recognition methodsShape correspondence and shape matchingPrincipal component analysis, feature extractionNeural network and Machine learning for image shape recognition