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Subject Syllabus

CB-803 (C) - Image Processing and Pattern Recognition

CSBS · Semester 8

Course Modules

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Image formation: Geometric and photometric models Digitization - sampling, quantization Image definition and its representation, neighbourhood metrics.

Intensity transformations and spatial filtering: Enhancement, contrast stretching, histogram specification, local contrast enhancement Smoothing, linear and order statistic filtering, sharpening, spatial convolution Gaussian smoothing DoG, LoG.

Segmentation: Pixel classification Grey level thresholding, global/local thresholding Optimum thresholding - Bayes analysis Otsu method Derivative based edge detection operators, edge detection/linking Canny edge detector Region growing, split/merge techniques, line detection Hough transform.

Image/Object features extraction: Textural features - gray level co-occurrence matrix Moments Connected component analysis Convex hull Distance transform, medial axis transform, skeletonization/thinning, shape properties.

Registration: Mono-modal/multimodal image registration Global/local registration Transform and similarity measures for registration Intensity/pixel interpolation.Colour image processing: Fundamentals of different colour models - RGB, CMY, HSI, YCbCr Lab False colour Pseudo colour Enhancement Segmentation.Morphological Filtering Basics: Dilation and Erosion Operators Top Hat Filters