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Full Description
This book is a companion book to the comprehensive text entitled Image Processing, Analysis, and Machine Vision by M. Sonka, V. Hlavac, and R. Boyle. This workbook provides additional material for readers of Sonka and is similarly structured. Written for students, teachers and practitioners to acquire practical understanding in a hands on fashion, this book provides the reader with short-answer questions, problems and selected algorithms from the main text using MATLAB in levels of varying difficulty. These resources can be used as extra practice for students to reinforce the material studied within the main text or can be useful as test materials for teachers. A solutions manual is available for Instructors for the problems within this workbook.
Contents
Preface0.1 ReferencesChapter 1 - Introduction1.1 ReferencesChapter 2 - The Image, its Representation and Properties2.1 Chapter Introduction2.2 Short-answer Questions2.3 Problems2.4 ReferencesChapter 3 - The Image, its Mathematical and Physical Background3.1 Chapter Introduction3.2 Short-answer Questions3.3 Problems3.4 ReferencesChapter 4 - Data Structures for Image Analysis4.1 Chapter Introduction4.2 Short-answer Questions4.3 Problems4.4 Co-occurrence matrix4.5 ReferencesChapter 5 - Image Pre-Processing5.1 Chapter Introduction5.2 Short-answer Questions5.3 Problems5.4 Gray-scale Transformation, Histogram Equalization5.5 Geometric Transformation5.6 Smoothing Using a Rotation Mask5.7 Image Sharpening by Using Laplacian5.8 Harris Corner Detector5.9 ReferencesChapter 6 - Segmentation I6.1 Chapter Introduction6.2 Short-answer Questions6.3 Problems6.4 References6.5 Iterative Threshold Selection6.6 Line Detection Using Hough Transform6.7 Dynamic Programming Boundary Tracing6.8 Region Merging via Boundary Melting 6.9 Removal of Small Regions Chapter 7 - Segmentation II7.1 Chapter Introduction7.2 Short-answer Questions7.3 Problems7.4 Mean Shift Segmentation7.5 Active Contours (snakes)7.6 Gradient Vector Flow Snakes7.7 Level Sets7.8 Graph Cut Segmentation7.9 ReferencesChapter 8 - Shape Representation and Description8.1 Chapter Introduction8.2 Short-answer Questions8.3 Problems8.4 ReferencesChapter 9 - Object Recognition9.1 Chapter Introduction9.2 Short-answer Questions9.3 Problems9.4 ReferencesChapter 10 - Image Understanding10.1 Chapter Introduction10.2 Short-answer Questions10.3 Problems10.4 ReferencesChapter 11 - 3D Vision, Geometry11.1 Chapter Introduction11.2 Short-answer Questions11.3 Problems11.4 Mathematical Description of a Camera11.5 Visualize a Camera in a 3D Plot11.6 Conversion of Rotation Parameters11.7 RQ Matrix Decomposition11.8 Homography Estimation From Point Correspondences -DLT Method11.8.1 Example of Homography Mapping11.9 Isotropic Point Normalization11.10 3D Point Reconstruction - Linear Method11.11 ReferencesChapter 12 - Use of 3D Vision12.1 Chapter Introduction12.2 Short-answer Questions12.3 Problems12.4 ReferencesChapter 13 - Mathematical Morphology13.1 Chapter Introduction13.2 Short-answer Questions13.3 Problems 13.4 ReferencesChapter 14 - Image Data Compression14.1 Chapter Introduction14.2 Short-answer Questions14.3 Problems 14.4 ReferencesChapter 15 - Texture15.1 Chapter Introduction15.2 Short-answer Questions15.3 Problems 15.4 ReferencesChapter 16 - Motion Analysis16.1 Chapter Introduction16.2 Short-answer Questions16.3 Problems16.4 Particle Filtering16.5 Kernel-Based Tracking16.6 References
