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

页码：207 / 211

页数：5

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