scholarly journals Special Edition. Pattern Recognition and Image Understanding. 2. Computational Theory for Image Understanding. 2-2 A Nice Way to Create Constraints for Vision. Extracting Multiple Visual Attributes.

1994 ◽  
Vol 48 (2) ◽  
pp. 135-141
Author(s):  
Masahiko Shizawa
Keyword(s):  
Pattern Recognition ◽  
Image Understanding ◽  
Special Edition ◽  
Computational Theory ◽  
Visual Attributes

A computational theory for movement pattern recognition based on optimal movement pattern generation

1995 ◽  
Vol 73 (1) ◽  
pp. 15-25 ◽  
Author(s):  
Yasuhiro Wada ◽  
Yasuharu Koike ◽  
Eric Vatikiotis-Bateson ◽  
Mitsuo Kawato
Keyword(s):  
Pattern Recognition ◽  
Movement Pattern ◽  
Pattern Generation ◽  
Computational Theory ◽  
Optimal Movement

scholarly journals Pattern Recognition & Image Understanding based on Fuzzy Technology

1997 ◽  
Vol 1 (1) ◽  
pp. 71-78 ◽  
Author(s):  
Kaoru Hirota ◽  
◽  
Yoshinori Arai ◽  
Yukiko Nakagawa ◽  
Keyword(s):  
Pattern Recognition ◽  
Time Use ◽  
Additional Data ◽  
Fuzzy Inference ◽  
Vision System ◽  
Image Understanding ◽  
Robot Arm ◽  
Remote Sensing Images ◽  
Dynamic Image ◽  
Hierarchical Pattern

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.

Machine learning paradigms for pattern recognition and image understanding

1996 ◽  
Vol 10 (1) ◽  
pp. 87-103 ◽  
Author(s):  
Terry Caelli ◽  
Walter F. Bischof
Keyword(s):  
Machine Learning ◽  
Pattern Recognition ◽  
Image Understanding
Sign in / Sign up

Export Citation Format

Share Document