Self-tuning fuzzy modeling with adaptive membership function, rules, and hierarchical structure based on genetic algorithm

1995 ◽  
Vol 71 (3) ◽  
pp. 295-309 ◽  
Author(s):  
Koji Shimojima ◽  
Toshio Fukuda ◽  
Yasuhisa Hasegawa
Author(s):  
Vamsi Krishna Madasu ◽  
Brian C. Lovell

This chapter presents an off-line signature verification and forgery detection system based on fuzzy modeling. The various handwritten signature characteristics and features are first studied and encapsulated to devise a robust verification system. The verification of genuine signatures and detection of forgeries is achieved via angle features extracted using a grid method. The derived features are fuzzified by an exponential membership function, which is modified to include two structural parameters. The structural parameters are devised to take account of possible variations due to handwriting styles and to reflect other factors affecting the scripting of a signature. The efficacy of the proposed system is tested on a large database of signatures comprising more than 1,200 signature images obtained from 40 volunteers.


2019 ◽  
Vol 361 ◽  
pp. 101-113 ◽  
Author(s):  
Moufid Bouhentala ◽  
Mouna Ghanai ◽  
Kheireddine Chafaa

Author(s):  
Dusan Popovic ◽  
Charalampos Moschopoulos ◽  
Ryo Sakai ◽  
Alejandro Sifrim ◽  
Jan Aerts ◽  
...  

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