反匹配:自动签名验证的神经网络方法

G. Hesketh
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引用次数: 5

摘要

COUNTERMATCH算法是一种弹性匹配神经网络模型,它试图将两个动态签名之间的所有对应点连接起来;签名就是一组有序的笔画,每一笔画都是由绘图板上的固定周期采样得出的一组有序的钢笔位置。一旦定义了点对点的对应关系,该算法就可以根据将一个签名转换为另一个签名所需的弹性变形量,在两个签名之间分配一个数值上的不相似度。然后,可以从从已知的真品和伪造匹配中得到的差异训练集构造一个简单(或复杂)的判别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Countermatch: A Neural Network Approach to Automatic Signature Verification
The COUNTERMATCH algorithm is an elastic matching neural network model which attempts to link all the corresponding points between two dynamic signatures; a signature is simply an ordered set of strokes, each stroke being an ordered list of inking pen positions derived from fixed period sampling on a graphics tablet. Once a point-for-point correspondence has been defined, the algorithm can assign a numerical dissimilarity between the two signatures on the basis of the amount of elastic deformation required to change one into the other. A simple (or complex) discriminant can then be constructed from a training set of dissimilarities derived from known authentic and forgery matches.
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