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One-class versus bi-class SVM classifier for off-line signature verification

机译:一类与两类SVM分类器进行离线签名验证

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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.
机译:支持向量机(SVM)已成为模式识别的替代工具,更具体地说是用于手写签名验证系统(HSVS)的工具。通常,双类SVM(B-SVM)用于在真实签名和伪造签名之间进行分隔。但是,实际上,只有真实的签名可用。在本文中,我们研究了使用一类SVM(OC-SVM)进行手写签名验证。在标准CEDAR数据库上进行的实验结果表明,与两类SVM相比,一类SVM的有效使用。

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