DocumentCode :
3627418
Title :
Off-line signature verification with PSO-NN algorithm
Author :
M. Taylan Das;L. Canan Dulger
Author_Institution :
Gaziantep University, Mechanical Engineering Department, 27310, Turkey
fYear :
2007
Firstpage :
1
Lastpage :
6
Abstract :
Analysis of signature is a widely used and developed area of research for personal verification. A typical signature verification system generally consists of four components: data acquisition, pre-processing, feature extraction and verification. This paper presents a novel technique for off-line signature verification (SV). The technique is based on a neural network (NN) approach trained with particle swarm optimization (PSO) algorithm. To test the performance of the proposed PSO-NN algorithm three types of forgeries; random, unskilled and skilled are examined and the experimental results are illustrated.
Keywords :
"Handwriting recognition","Forgery","Feature extraction","Data acquisition","Testing","Image processing","Data mining","Neural networks","Biometrics","Mechanical engineering"
Publisher :
ieee
Conference_Titel :
Computer and information sciences, 2007. iscis 2007. 22nd international symposium on
Print_ISBN :
978-1-4244-1363-8
Type :
conf
DOI :
10.1109/ISCIS.2007.4456842
Filename :
4456842
Link To Document :
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