Masters of Computer Applications:Image Processing and Computer VisionThapar University
Price on request
Frequent Asked Questions
Recognised Bachelors degree of minimum 3 years duration in any discipline with Mathematics at least at 10+2 school level and has also qualified in the Entrance Test to be conducted by the University.OR Recognised Bachelor's Degree of minimum 3 years duration in any discipline with Mathematics as one of the subjects and has also qualified in the Entrance Test to be conducted by the University.
Discrete Mathematical Structures
Elements of Electronics Engineering
Problem Solving and Programming in C
Computer Organization and Architecture
Fundamental of Microprocessors and Interfacing
Object Oriented Programming using c++ and Java
System Analysis and Design
Statistics and Combinatorics
Data Base Management System
Design and Analysis of Algorithms
Advanced Java and Network Programming
Computer Graphics and Multimedia
ERP and Tools
Information and Network Security
Software Project Management
Net Framework and C# Programming
System Development Project
Image Processing and Computer Vision
Introduction: Image analysis and computer vision, Imaging systems, Fundamental Steps in Image Processing, Elements of Digital image processing systems, Sampling and quantization, some basic relationships like neighbours, connectivity, Distance measure between pixels, Imaging Geometry.
Image Transforms: Discrete Fourier Transform, Some properties of the two-dimensional Fourier transform, Fast Fourier transform, Inverse FFT, Wavelet transforms.
Image Enhancement: Spatial domain methods, Frequency domain methods, Enhancement by point processing, Spatial filtering, Lowpass filtering, Highpass filtering, Homomorphic filtering, Colour Image Processing.
Image Restoration: Degradation model, Diagnolization of Circulant and Block-Circulant Matrices, Algebraic Approach to Restoration, Inverse filtering, Wiener filter, Constrained Least Square Restoration, Interactive Restoration, Restoration in Spatial Domain.
Image Compression: Coding, Interpixel and Psychovisual Redundancy, Image Compression models, Error free comparison, Lossy compression, Image compression using wavelets, Image compression standards.
Image Segmentation: Detection of Discontinuities, Edge linking and boundary detection, Thresholding, Region Oriented Segmentation, Motion based segmentation.
Representation and Description: Representation schemes like chain coding, Polygonal Approximation, Signatures, Boundary Segments, Skeleton of region, Boundary description, Regional descriptors, Morphology.
Recognition and Interpretation: Elements of Image Analysis, Pattern and Pattern Classes, Decision-Theoretic Methods, Structural Methods, Interpretation.
Laboratory Work: The lab work will be based on operations on images. The programs will be based on image enhancement, image zooming, image cropping, image restoration, image compression and image segmentation etc.