Computer Vision and Fuzzy-Neural Systems - Hardcover

Über die Autorin bzw. den Autor

Dr. Arun D. Kulkarni is Professor of Computer Science at The University of Texas at Tyler, Tyler, Texas. His research interests include computer vision, fuzzy-neural systems, data mining, image processing, and artificial intelligence. He has authored a book and published more than 50 referred papers. His awards include the 1984 Fulbright Fellowship award and the 1997 NASA/ASSE Summer Faculty Fellowship. Dr. Kulkarni obtained his Ph.D. from the Indian Institute of Technology, Bombay, and was a post-doctoral fellow at Virginia Tech.

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• New computer vision techniques based on neural networks, fuzzy inference systems, and fuzzy-neural network models
• Detailed tutorials, hands-on exercises, real-world examples, and proven algorithms

CD-ROM: code libraries for the MATLAB neural network, fuzzy logic, and image processing toolboxes, test images from Kodak and Space Imaging, and more.

The first complete guide to applying fuzzy-neural systems in computer vision.

Recent advances in neural networks and fuzzy logic are transforming the field of computer vision, making it possible for computer vision applications to learn much as the brain does, and to handle imprecise visual data far more effectively. Now, Dr. Arun D. Kulkarni brings together the field's latest research and applications, presenting the field's first comprehensive tutorial and reference.

Kulkarni starts by reviewing the fundamentals of computer vision, and the stages of a computer vision system. He shows how these stages have traditionally been implemented via statistical techniques; then introduces approaches that incorporate neural networks, fuzzy inference systems, and fuzzy-neural network models. Coverage includes:

• Preprocessing techniques such as radiometric or geometric corrections
• Feature extraction, supervised and unsupervised classification, associative memories, and other techniques for improving accuracy and performance
• Key computer vision applications: remote sensing, medical imaging, compression, data mining, character recognition, stereovision, and more

Computer Vision and Fuzzy-Neural Systems illuminates the state-of-the-art through hands-on exercises, real-world examples, and proven algorithms. It's an essential resource for every engineer, scientist, and programmer working in computer vision and a wide range of related fields. It can also be used as a textbook for undergraduate- or graduate-level courses in computer vision.

Contains extensive library of MATLAB command files, executable files for some useful programs, and test images from Kodak and Space Imaging.