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Full Description
The textbook is primarily written for senior undergraduate and post graduate students studying in areas of computer science and engineering, and electrical engineering. However, as the subject covers various interdisciplinary areas, the book is also expected to be of interest to a larger readership in Science and Engineering. It has a comprehensive and balanced coverage of theory and applications of computer vision with a textbook approach providing worked out examples, and exercises. It covers theory and applications of some relatively recent advancements in technology such as on colour processing, deep learning techniques for processing images and videos, document processing, biometry, content based image retrieval, etc. It also delves with theories and processing in non-optical imaging systems, such as range or depth imaging, medical imaging and remote sensing imaging.
Contents
Preface; Acknowledgements; Part I. Visual Information Processing: Chapter 1. Fundamentals of Image and Video Processing; Chapter 2. Alternate Representations of Images and Videos; Chapter 3. Color Processing; Chapter 4. Feature Detection, Matching and Model Fitting; Chapter 5. Visual Saliency and Cognitive Processing; Chapter 6. Clustering and Segmentation; Chapter 7. Classification; Chapter 8. Object Tracking; Chapter 9. Deep Visual Learning; Part II. Vision Geometry: Chapter 10. Two-dimensional Projective Geometry; Chapter 11. Single View Camera Geometry; Chapter 12. Stereo Vision; Part III. Non-Optical Vision: Chapter 13. Range Imaging; Chapter 14. Medical Imaging; Chapter 15. Remote Sensing; Part IV. Applications: Chapter 16. Document Processing; Chapter 17. Biometry; Chapter 18. Content Based Image Retrieval; Bibliography; Index.
