Ferrer Miguel A, Alonso Jesús B, Travieso Carlos M
Departamento de Señales y Comunicaciones, Universidad de Las Palmas de Gran Canaria, Campus de Tafira, E35017 Las Palmas de Gran Canaria, Spain.
IEEE Trans Pattern Anal Mach Intell. 2005 Jun;27(6):993-7. doi: 10.1109/TPAMI.2005.125.
This paper presents a set of geometric signature features for offline automatic signature verification based on the description of the signature envelope and the interior stroke distribution in polar and Cartesian coordinates. The features have been calculated using 16 bits fixed-point arithmetic and tested with different classifiers, such as hidden Markov models, support vector machines, and Euclidean distance classifier. The experiments have shown promising results in the task of discriminating random and simple forgeries.
本文基于签名包络的描述以及极坐标和笛卡尔坐标下内部笔画分布,提出了一组用于离线自动签名验证的几何特征。这些特征已使用16位定点算法进行计算,并使用不同的分类器进行测试,如隐马尔可夫模型、支持向量机和欧几里得距离分类器。实验表明,在区分随机伪造和简单伪造的任务中取得了有前景的结果。