ISBN : 9781032071299
Author : Scott E Umbaugh
Publisher : CRC
Year : 2023
Language : English
Type : Book
Description : 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. Table of Contents 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