One-Class versus Bi-Class SVM Classifier for Off-line Signature Verification

被引：0
|
作者：
Guerbai, Yasmine [1 ]
Chibani, Oucef [1 ]
Abbas, Nassim [1 ]
机构：
[1] USTHB, Speech Commun & Signal Proc Lab, Fac Elect & Comp Sci, Algiers, Algeria
来源：
2012 INTERNATIONAL CONFERENCE ON MULTIMEDIA COMPUTING AND SYSTEMS (ICMCS) | 2012年
关键词：
signature verification; one class support vector machine; bi-class support vector machine; uniform grid; SUPPORT;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Support vector machines (SVMs) have become an alternative tool for pattern recognitions, and more specifically for Handwritten Signature Verification Systems (HSVS). Usually, the bi-class SVMs (B-SVM) are used for separating between genuine and forged signatures. However, in practice, only genuine signatures are available. In this paper, we investigate the use of one-class SVM (OC-SVM) for handwritten signature verifications. Experimental results conducted on the standard CEDAR database show the effective use of the one-class SVM compared to the bi-class SVM.
引用
收藏
页码：207 / 211
页数：5
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