Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Zaki, Mohammed | El-Ramsisi, Abdallah | Omran, Rostom
Affiliations: Al-Azhar University, Cairo, Egypt | Air Force R&D Center, Cairo, Egypt | EgyptAir, Information Technology Sector, Cairo, Egypt
Abstract: An efficient pattern recognition system based on soft computing concepts has been developed. A new reliable genetic stereo vision algorithm is used in order to estimate depth of objects without using any point-to-point correspondence. Instead, correspondence of the contours as a whole is required. Invariant breakpoints are located on a shape contour using the colinearity principle. Thus, a localized representation of a shape contour including 3-D moments as well as a chain code can be obtained. This representation is invariant to rotation, translation, scale, and starting point. The system is provided with a neural network classifier and a dynamic alignment procedure at its output. Combing the robustness of neural network classifier with the genetic algorithm capability results in a reliable pattern recognition system which can tolerate high degrees of noise and occlusion levels. The performance of the system has been demonstrated using five different types of aircraft and the experimental results are reported.
Journal: Journal of Intelligent and Fuzzy Systems, vol. 9, no. 1-2, pp. 85-99, 2000
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]