DocumentCode :
2782855
Title :
The methods of personal features selection using ACOGA and geometric extrema characteristics for Chinese online signature verification
Author :
Cheng, Guozhong ; Wei, Feng
Author_Institution :
Sch. of Math. & Inf., Chinawest Normal Univ., Nanchong, China
fYear :
2009
fDate :
6-8 Nov. 2009
Firstpage :
562
Lastpage :
565
Abstract :
This paper presents a new method to select a segment-to-segment matching by analysing signature verification, accordingly curve segments used in signature verification and the regional feature contained in the curve segment are picked-up and the regional features are selected by ant colony optimization (ACO) algorithm and genetic algorithms(GAs). Namely, features selected are first encoded into chromosome, and descendible types are founded by ACOGA improved locally. The essential advantages of ACO including cooperativity, obustness, positive feedback and distributed nature were discuss and also the disadvantages of low convergence speed while the high adaptability of GAs were discussed too. Meanwhile, cross operation and mutation of genetic algorithms were introduced into the ACO. A new crossover method is also proposed to determine the number of curve segments. The experiment shows that the algorithms proposed can accurately find optimal features for signature verification and bring the lower FRR and FAR, thereby the veracity in online signature verification is enhanced.
Keywords :
feature extraction; genetic algorithms; handwriting recognition; image coding; image matching; image segmentation; ACOGA; Chinese online signature verification; ant colony optimization; encoding; genetic algorithms; geometric extrema characteristics; personal features selection; segment-to-segment matching; Algorithm design and analysis; Ant colony optimization; Biological cells; Educational institutions; Eigenvalues and eigenfunctions; Flowcharts; Genetics; Handwriting recognition; Hidden Markov models; Mathematics; ACO; GAs; Geometric Extrema; Personal Features Selection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Network Infrastructure and Digital Content, 2009. IC-NIDC 2009. IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4898-2
Electronic_ISBN :
978-1-4244-4900-6
Type :
conf
DOI :
10.1109/ICNIDC.2009.5360930
Filename :
5360930
Link To Document :
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