Understanding Digital Image Processing

This book introduces the fundamental concepts of modern digital image processing. It aims to help the students, scientists, and practitioners to understand the concepts through clear explanations, illustrations and examples. The discussion of the general concepts is supplemented with examples from applications and ready-to-use implementations of concepts in MATLAB®. Program code of some important concepts in programming language 'C' is provided. To explain the concepts, MATLAB® functions are used throughout the book. MATLAB® Version 9.3 (R2017b), Image Acquisition Toolbox Version 5.3 (R2017b), Image Processing Toolbox, Version 10.1 (R2017b) have been used to create the book material. Meant for students and practicing engineers, this book provides a clear, comprehensive and up-to-date introduction to Digital Image Processing in a pragmatic manner.

Table of Contents Introduction to Digital Image Processing Introduction Typical Image Processing Operations History of Digital Image Processing Human Visual System Classification of Digital images Digital Image File Types Components of an Image Processing system Applications of Digital Image Processing Summary Digital Image representation Digital Image Sampling and Quantization Color models Basic Relationships between pixels Adjacency Digital Path Connected set Summary Mathematical Tools for Image Processing Introduction Distance Function Convexity Property Topological Properties Interpolation Circularly symmetric signals Statistics Transforms Wavelet Transform Discrete Cosine Transform Walsh Transform Matrix Operations Set Theory Summary Image Enhancement in Spatial Domain Introduction Point Processing Mask Processing Smoothing Filters Sharpening Filters Bit-plane slicing Arithmetic operations Logical Operations Geometric Operations Image padding Histogram and Histogram processing Summary Image Processing in Frequency Domain Introduction Low-Pass Filtering in Frequency Domain High-Pass Filtering High-Frequency Emphasis Filter Summary Image Denoising Introduction Image Noise Types Image Denoising Performance Evaluation of Denoising Techniques Summary Image Segmentation Introduction Techniques of Image Segmentation Discontinuity-based Image Segmentation Techniques Thresholding-based image segmentation Region-based image segmentation Watershed-based image segmentation Summary Mathematical Morphology Introduction Morphological Operations Summary Image Understanding Introduction Contour-based shape representation and description Boundary Segments Description Object Recognition Summary Image Compression Introduction History of compression technologies Image File types Compression quality measures Image Redundancy Fundamental Building Blocks of Image Compression Image compression model Image compression standards Summary Image Retrieval Introduction Text Based Image Retrieval System Content based image retrieval systems Image pre-processing Feature Extraction Feature selection Similarity measure and performance evaluation Summary Digital Image Forgery Introduction History of image forgery Image forgery detection techniques Summary Appendix A Appendix B Appendix C

Vipin Tyagi, Fellow-IETE, is currently working as Professor in Computer Science and Engineering and Head- Faculty of Mathematical Sciences at the Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India. He is the Vice President of the Computer Society of India (CSI) of Region 3 andis also associated with the CSI Special Interest Group on Cyber Forensics. He was President of the Engineering Sciences Section of the Indian Science Congress Association (ISCA) for the term 2010–11. He has publishedseveral books and a number of papers in various prominent journals and advanced research series, and is a recognized expert in the areas of image processing, cyber security and cyber forensics. He can be reached at dr.vipin.tyagi@gmail.com.