Rough set approach to online signature identification

被引：24

作者：

Al-Mayyan, Waheeda ^{[1
]}

Own, Hala S. ^{[2
]}

Zedan, Hussein ^{[1
]}

机构：

[1] De Montfort Univ, Software Technol Res Lab, Leicester LE1 9BH, Leics, England

[2] Natl Res Inst Astron & Geophys, Dept Solar & Space Res, Cairo, Egypt

来源：

DIGITAL SIGNAL PROCESSING | 2011年 / 21卷 / 03期

关键词：

Biometric recognition; Online signature identification; Rough set; Naive Bayes; Feature reduction; Classification; VERIFICATION;

D O I：

10.1016/j.dsp.2011.01.007

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents an online signature identification system based on global features. The information is extracted as time functions of various dynamic properties of the signatures. A database of 2160 signatures from 108 subjects was built. Thirty-one features were identified and extracted from each signature. Different feature reduction approaches and classifiers were used to assess their suitability for this application. Rough set approach has resulted in a reduced set of nine features that were found to capture the essential characteristics required for signature identification. Rough set classifier has achieved 100% correct classification rate, which demonstrates its suitability and effectiveness for online signature identification. (C) 2011 Elsevier Inc. All rights reserved.

引用

页码：477 / 485

页数：9

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