Preface. Contributing Authors. 1. Summation; A. Rosenfeld. 2. Digital Geometry - The Birth of a New Discipline; R. Klette. 3. Digital Topology; T.Y. Kong. 4. Fuzzy Mathematics; J.N. Mordeson. 5. Picture Languages; A. Nakamura. 6. Parallel Image Processing; A.Y. Wu. 7. Object Representations; H. Samet. 8. Texture Classification and Segmentation; R. Chellappa, B.S. Manjunath. 9. Edge Measures Using Similarity Regions; M.K. Singh, N. Ahuja. 10. Relaxation Labeling: 25 Years and Still Iterating; S.W. Zucker. 11. From a Robust Hierarchy to a Hierarchy of Robustness; P. Meer. 12. A Pyramid Framework for Real-Time Computer Vision; P.J. Burt. 13. On the Computational Modeling of Human Vision; J. Beck. 14. Statistics Explains Geometrical Optical Illusions; C. Fermüller, Y. Aloimonos. 15. Optics for OmniStereo Imaging; Y. Pritch, et al. 16. Volumetric Scene Reconstruction from Multiple Views; C.R. Dyer. Index.
Computer systems that analyze images are critical to a wide variety of applications such as visual inspections systems for various manufacturing processes, remote sensing of the environment from space-borne imaging platforms, and automatic diagnosis from X-rays and other medical imaging sources. Professor Azriel Rosenfeld, the founder of the field of digital image analysis, made fundamental contributions to a wide variety of problems in image processing, pattern recognition and computer vision. Professor Rosenfeld's previous students, postdoctoral scientists, and colleagues illustrate in Foundations of Image Understanding how current research has been influenced by his work as the leading researcher in the area of image analysis for over two decades.
Each chapter of Foundations of Image Understanding is written by one of the world's leading experts in his area of specialization, examining digital geometry and topology (early research which laid the foundations for many industrial machine vision systems), edge detection and segmentation (fundamental to systems that analyze complex images of our three-dimensional world), multi-resolution and variable resolution representations for images and maps, parallel algorithms and systems for image analysis, and the importance of human psychophysical studies of vision to the design of computer vision systems. Professor Rosenfeld's chapter briefly discusses topics not covered in the contributed chapters, providing a personal, historical perspective on the development of the field of image understanding.
Foundations of Image Understanding is an excellent source of basic material for both graduate students entering the field and established researchers who require a compact source for many of the foundational topics in image analysis.
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