Off-line signature verification with PSO-NN algorithm

被引：0
|
作者：
Das, A. Taylan [1 ]
Dulger, L. Canan [1 ]
机构：
[1] Gaziantep Univ, Dept Mech Engn, TR-27310 Gaziantep, Turkey
来源：
2007 22ND INTERNATIONAL SYMPOSIUM ON COMPUTER AND INFORMATION SCIENCES | 2007年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：92 / 97
页数：6
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