Contents Preface. 1. Introduction. 2. The image model. 3. Image acquisition. 4. Image presentation. 5. Statistical operations. 6. Spatial operations and transformations. 7. Segmentation and edge detection. 8. Morphological and other area operations. 9. Finding basic shapes. 10. Labelling lines and regions. 11. Reasoning facts and inferences. 12. Pattern recognition and training. 13. The frequency domain. 14. Applications of frequency domain processing. 15. Image compression. 16. Texture. 17. Other topics. 18. Applications. Bibliography. Index. This book is a major update of Prof. Adrian Low's First Edition entitled Introductory Computer Vision and Image Processing published by McGraw Hill in 1991. Since the first edition was published there has been a fantastic number of developments in the underlying theory techniques and applications in computer vision and image processing. The Second Edition brings the science of image up to date but still maintains the gentle approach avoiding substantial mathematics. Recognising that many students want an intuitive understanding rather than a detailed exposition the book develops ideas in a readable and user friendly language adding code where sensible so that the student can incorporate the ideas into projects without having to recreate the wheel themselves. Main Features Focussed on small images and few colours precisely so that algorithms can be explained using real numbers and not just formulate. Adding new techniques that will help those seeking algorithms to do imaging. Deconvolution sections on compression morphing and warping have been added. Described the subject to less mathematical students. 300 pp.

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Title: Introductory Computer Vision Imaging Techniques and Solutions (Reprint)
Publisher: BS Pub
Publication Date: 2022
Binding: Soft cover
Edition: 2nd Edition
Condition: New

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