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This graduate textbook explains image reconstruction technologies based on region-based binocular and trinocular stereo vision, and object, pattern and relation matching. It further discusses principles and applications of multi-sensor fusion and content-based retrieval. Rich in examples and excises, the book concludes image engineering studies for electrical engineering and computer science students.
Price: $93.99
Pages: 312
Publisher: De Gruyter
Imprint: De Gruyter
Series: De Gruyter Textbook
Publication Date:
07 August 2017
ISBN: 9783110520347
Format: Paperback
BISACs:
COM012050 COMPUTERS / Image Processing, COM018000 COMPUTERS / Data Processing, COM021030 COMPUTERS / Database Management / Data Mining
Yujin Zhang, Tsinghua University, Beijing, China
Table of Content:
Chapter 1 Stereo Vision
1.1 Modules of Stereo Vision
1.2 Region-Based Binocular Matching
1.3 Feature-Based Binocular Matching
1.4 Horizontal Multiple Stereo Matching
1.5 Orthogonal Trinocular Matching
1.6 Computing Sub-Pixel Level Disparity
1.7 Error Detection and Correction
1.8 Summary
Problems, Further Reading
Chapter 2 3-D Shape Information Recover
2.1 Photometric Stereo
2.2 Structure from Motion
2.3 Shape from Shading
2.4 Texture and Surface Orientation
2.5 Depth from Focal Length
2.6 Pose from Three Pixels
2.7 Summary
Problems, Further Reading
Chapter 3 Matching and Understanding
3.1 Fundamental of Matching
3.2 Object Matching
3.3 Dynamic Pattern Matching
3.4 Relation Matching
3.5 Graph Isomorphism
3.6 Labeling of Line Drawings
3.7 Summary
Problems, Further Reading
Chapter 4 Multi-Sensor Image Fusion
4.1 Overview of Information Fusion
4.2 Image Fusion
4.3 Pixel-Layer Fusion
4.4 Feature-Layer and Decision-Layer Fusions
4.5 Summary
Problems, Further Reading
Chapter 5 Content-Based Image Retrieval
5.1 Feature-Based Image Retrieval
5.2 Motion-Feature-Based Video Retrieval
5.3 Object-Based Retrieval
5.4 Video Analysis and Retrieval
5.5 Summary
Problems, Further Reading
Chapter 1 Stereo Vision
1.1 Modules of Stereo Vision
1.2 Region-Based Binocular Matching
1.3 Feature-Based Binocular Matching
1.4 Horizontal Multiple Stereo Matching
1.5 Orthogonal Trinocular Matching
1.6 Computing Sub-Pixel Level Disparity
1.7 Error Detection and Correction
1.8 Summary
Problems, Further Reading
Chapter 2 3-D Shape Information Recover
2.1 Photometric Stereo
2.2 Structure from Motion
2.3 Shape from Shading
2.4 Texture and Surface Orientation
2.5 Depth from Focal Length
2.6 Pose from Three Pixels
2.7 Summary
Problems, Further Reading
Chapter 3 Matching and Understanding
3.1 Fundamental of Matching
3.2 Object Matching
3.3 Dynamic Pattern Matching
3.4 Relation Matching
3.5 Graph Isomorphism
3.6 Labeling of Line Drawings
3.7 Summary
Problems, Further Reading
Chapter 4 Multi-Sensor Image Fusion
4.1 Overview of Information Fusion
4.2 Image Fusion
4.3 Pixel-Layer Fusion
4.4 Feature-Layer and Decision-Layer Fusions
4.5 Summary
Problems, Further Reading
Chapter 5 Content-Based Image Retrieval
5.1 Feature-Based Image Retrieval
5.2 Motion-Feature-Based Video Retrieval
5.3 Object-Based Retrieval
5.4 Video Analysis and Retrieval
5.5 Summary
Problems, Further Reading