Handbook of Pattern Recognition and Computer Vision
Pattern recognition and computer vision and their applications have
experienced enormous progress in research and development over the
last two decades. This comprehensive handbook documents both the
basics and new and advanced results in the field. The chapters,
written by leading experts, cover the major topic areas.
Researchers, students and users of pattern recognition and computer
vision should find the book a valuable reference for help in
understanding the many techniques available, the systems already
developed, as well as the basic principles behind many topic areas.
Part 1 Basic methods in pattern recognition: statistical pattern recognition K. Fukunaga; large-scale feature selection J. Sklansky and W. Siedlecki. Part 2 Basic method in image processing and vision: vision engineering - designing computer vision systems R. Chellapa and A. Rosenfeld; colour in computer vision Q-T. Luong; model-based texture segmentation R. Chellapa et al; positional estimation techniques for an autonomous mobile robot - a review R. Talluri and J.K. Aggarwal. Part 3 Recognition applications: pattern recognition in geophysical signal processing and interpretation Y. Li et al; optical handwritten Chinese character recognition J.S. Huang. Part 4 Inspection and robotic applications: computer vision in food handling and sorting H. Arnason and M. Asmundsson; quantitative 3-D methods in medical imaging M. Loew. Part 5 Architectures and technology: optical pattern recognition for computer vision D. Casasent; connectionist architectures in low-level image segmentation W. Blanz and S. Gish.