4th Edition
Digital Image Processing and Analysis Computer Vision and Image Analysis
Computer Vision and Image Analysis, focuses on techniques and methods for image analysis and their use in the development of computer vison applications. The field is advancing at an ever increasing pace, with applications ranging from medical diagnostics to space exploration. The diversity of applications is one of the driving forces that make it such an exciting field to be involved in for the 21st century. This book presents a unique engineering approach to the practice of computer vision and image analysis, which starts by presenting a global model to help gain an understanding of the overall process, followed by a breakdown and explanation of each individual topic. Topics are presented as they become necessary for understanding the practical imaging model under study, which provides the reader with the motivation to learn about and use the tools and methods being explored.
The book includes chapters on image systems and software, image analysis, edge, line and shape detection, image segmentation, feature extraction and pattern classification. Numerous examples, including over 500 color images are used to illustrate the concepts discussed. Readers can explore their own application development with any programming languages, including C/C++, MATLAB®, Python, and R, and software is provided for both the Windows/C/C++ and MATLAB®environments.
The book can be used by the academic community in teaching and research, with over 700 PowerPoint Slides and a complete Solutions Manual to the over 150 included problems. It can also be used for self-study by those involved with developing computer vision applications, whether they are engineers, scientists or artists. The new edition has been extensively updated and includes numerous problems and programming exercises that will help the reader and student to develop their skills.
Chapter 1: Digital Image Processing and Analysis
1.1 Introduction
1.2 Image Analysis and Computer Vision Overview
1.3 Digital Imaging Systems
1.4 Image Formation and Sensing
1.5 Image Representation
1.6 Key Points
1.7 References and Further Reading
1.8 Exercises
Chapter 2: Computer Vision Development Tools
2.1 Introduction and Overview
2.2 CVIPtools Windows GUI
2.3 CVIPlab for C/C++ Programming
2.4 The Matlab CVIP Toolbox
2.5 References and Further Reading
2.6 Introductory Programming Exercises
2.7 Computer Vision and Image Analysis Projects
CHAPTER 3: Image Analysis and Computer Vision
3.1 Introduction
3.2 Preprocessing
3.3 Binary Image Analysis
3.4 Key Points
3.5 References and Further Reading
3.6 Exercises
3.7 Supplementary Exercises
Chapter 4: Edge, Line and Shape Detection
4.1 Introduction and Overview
4.2 Edge Detection
4.3 Line Detection
4.4 Corner and Shape Detection
4.5 Key Points
4.6 References and Further Reading
4.7 Exercises
4.8 Supplementary Exercises
Chapter 5: Segmentation
5.1 Introduction and Overview
5.2 Region Growing and Shrinking
5.3 Clustering Techniques
5.4 Boundary Detection
5.5 Deep Learning Segmentation Methods
5.6 Combined Segmentation Approaches
5.7 Morphological Filtering
Chapter 6: Feature Extraction and Analysis
6.1 Introduction and Overview
6.2 Shape Features
6.3 Histogram Features
6.4 Color Features
6.5 Fourier Transform and Spectral Features
6.6 Texture Features
6.7 Region Based Features: SIFT/SURF/GIST
6.8 Feature Extraction with CVIPtools
6.9 Feature Analysis
6.10 Key Points
6.11 References and Further Reading
6.12 Exercises
6.13 Supplementary Exercises
Chapter 7: Pattern Classification
7.1 Introduction
7.2 Algorithm Development: Training and Testing Methods
7.3 Nearest Neighbor (NN), K-NN, Nearest Centroid, Template Matching
7.4 Bayesian, Support Vector Machines, Random Forest Classifiers
7.5 Neural Networks and Deep Learning
7.6 Cost/Risk Functions and Success Measures
7.7 Pattern Classification Tools: Python, R, Matlab, CVIPtools
7.8 Key Points
7.9 References and Further Reading
7.10 Exercises
7.11 Supplementary Exercises
Chapter 8: Application Development Tools
8.1 Introduction and Overview
8.2 CVIP Algorithm Test and Analysis Tool
8.3 CVIP-ATAT: Application Development Necrotic Liver Tissue
8.4 CVIP-ATAT: Application Development with Fundus Images
8.5 CVIP-ATAT: Automatic Mask Creation of Gait Images
8.6 CVIP Feature Extraction and Pattern Classification Tool
8.7 CVIP-FEPC: Application Development with Thermograms
8.8 CVIP-FEPC: Identification of Bone Cancer in Canine Thermograms
8.9 Matlab CVIP Toolbox GUI: Detection of syrinx in canines with Chiari malformation via Thermograms
Biography
Dr. Scott E Umbaugh is a distinguished research professor of Electrical and Computer Engineering and Graduate Program director for the Department of Electrical and Computer Engineering at Southern Illinois University Edwardsville (SIUE). He is also the director of the Computer Vision and Image Processing (CVIP) Laboratory at SIUE. He has been teaching computer vision and image processing, as well as computer and electrical engineering design, for over 30 years. His professional interests include computer vision and image processing education, research and development of both human and computer vision applications, and engineering design education.
Prior to his academic career, Dr. Umbaugh worked as a computer design engineer and project manager in the avionics and telephony industries. He has been a computer imaging consultant since 1986 and has provided consulting services for the aerospace, medical and manufacturing industries with projects ranging from automatic identification of defects in microdisplay chips to analysis of thermographic images for clinical diagnosis of brain disease. He has performed research and development for projects funded by the National Institutes of Health, the National Science Foundation and the U. S. Department of Defense.
Dr. Umbaugh is author or co-author of numerous technical papers, two edited books, and multiple editions of his textbooks on computer vison and image processing. His books are used at academic and research organizations throughout the world. He has served on editorial boards and as a reviewer for a variety of IEEE journals and has evaluated research monographs and textbooks in the imaging field.
Dr. Umbaugh received his B.S.E. degree with honors from Southern Illinois University Edwardsville in 1982, M.S.E.E. in 1987 and Ph.D. in 1990 from the Missouri University of Science and Technology, where he was a Chancellor's Fellow. He is a senior member of the Institute of Electrical and Electronic Engineers (IEEE), a member of Sigma Xi and the International Society for Optical Engineering (SPIE). Dr. Umbaugh is also the primary developer of the CVIPtools software package and the associated CVIP MATLAB Toolbox.
