JACIII Vol.1 No.1 pp. 71-78
doi: 10.20965/jaciii.1997.p0071


Pattern Recognition & Image Understanding based on Fuzzy Technology

Kaoru Hirota*, Yoshinori Arai**, Yukiko Nakagawa*

*Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama 226, Japan

**Tokyo Institute of Polytechnics, 1583 Iiyama, Atsugi-shi, Kanagawa 243-02, Japan

April 20, 1997
May 20, 1997
October 20, 1997
Fuzzy, Pattern recognition, Image understanding, Clustering, Robot vision

Four image recognition and understanding techniques based on fuzzy technology developed by the authors group have been surveyed. First topics is a fuzzy clustering with additional data applied to the remote sensing images. It is modified version of the well known FCM. A robot arm and vision system on assembling line is presented using fuzzy discriminant tree for a real time use. The repetition method is introduced into the construction of discriminant tree. Third is the pattern recognition for a models of cars which is applied a fuzzy hierarchical pattern recognition based on fixation feedback. Finally, a fuzzy dynamic image understanding system is presented using fuzzy knowledge base and fuzzy inference method to understand dynamic image understanding on general roads in Japan. These techniques are mentioned the algorithms, and some of them are with experimental results.

Cite this article as:
Kaoru Hirota, Yoshinori Arai, and Yukiko Nakagawa, “Pattern Recognition & Image Understanding based on Fuzzy Technology,” J. Adv. Comput. Intell. Intell. Inform., Vol.1, No.1, pp. 71-78, 1997.
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Last updated on Feb. 25, 2021