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.
Autorentext
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 and is 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 published several 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.
Inhalt
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