Guru D S, Prakash H N
Department of Studies in Computer Science, Manasagangotri, University of Mysore, Mysore 570 006, India.
IEEE Trans Pattern Anal Mach Intell. 2009 Jun;31(6):1059-73. doi: 10.1109/TPAMI.2008.302.
In this paper, we propose a new method of representing on-line signatures by interval valued symbolic features. Global features of on-line signatures are used to form an interval valued feature vectors. Methods for signature verification and recognition based on the symbolic representation are also proposed. We exploit the notions of writer dependent threshold and introduce the concept of feature dependent threshold to achieve a significant reduction in equal error rate. Several experiments are conducted to demonstrate the ability of the proposed scheme in discriminating the genuine signatures from the forgeries. We investigate the feasibility of the proposed representation scheme for signature verification and also signature recognition using all 16500 signatures from 330 individuals of the MCYT bimodal biometric database. Further, extensive experimentations are conducted to evaluate the performance of the proposed methods by projecting features onto Eigenspace and Fisherspace. Unlike other existing signature verification methods, the proposed method is simple and efficient. The results of the experimentations reveal that the proposed scheme outperforms several other existing verification methods including the state-of-the-art method for signature verification.
在本文中，我们提出了一种通过区间值符号特征来表示在线签名的新方法。在线签名的全局特征被用于形成区间值特征向量。还提出了基于符号表示的签名验证和识别方法。我们利用依赖于书写者的阈值概念，并引入依赖于特征的阈值概念，以显著降低等错误率。进行了多项实验，以证明所提出方案区分真实签名和伪造签名的能力。我们使用MCYT双峰生物特征数据库中330个人的全部16500个签名，研究了所提出的表示方案用于签名验证以及签名识别的可行性。此外，通过将特征投影到特征空间和Fisher空间，进行了广泛的实验来评估所提出方法的性能。与其他现有的签名验证方法不同，所提出的方法简单且高效。实验结果表明，所提出的方案优于其他几种现有的验证方法，包括签名验证的最新方法。
