摘要
根据签名动态信息进行签名认证可以提高认证系统的安全性 ,它是在由签名动态信息的特征值张成的特征空间上的分类问题 .然而 ,签名动态信息时间序列的时间弯曲现象使得特征值分散 ,不容易在特征空间上确定出真签名的特征值稳定的子空间 ,在签名样本数量小时尤为如此 .因此提出一种非线性局部寻优时间弯曲校正方法 ,它具有较好的校正效果和较低的计算复杂度 .利用它对签名样本的动态信息时间序列进行校正 ,可以提高签名特征向量在特征空间上分布的聚拢性 ,拉开真、伪签名特征向量在特征空间上的距离 .综合利用非线性局部寻优时间弯曲校正方法和线性时间弯曲校正方法对有限数量的标准签名样本进行处理 ,可在特征空间划分出不同置信度的特征稳定的子空间 。
Using dynamic information of signing to verify signatures can raise the safety of verifying systems. It is a problem of vector classification in the space spanned by the dynamic features of handwritten signatures. However, the discrete-time signals of sample signatures are usually warped to different extent at different positions, which distorts the distribution of the feature vectors obtained from these signals in feature space. Therefore, it is difficult to determine the stable subspace that separates the genuine signatures from forgery ones. This situation becomes worse when the total number of sample signatures is low. In this paper, a nonlinear local optimal time warping algorithm is put forward, which has low computational complexity but with good performance. It can effectively increase the compactness of the feature vectors of genuine signatures, and therefore enlarge the distance from the feature vectors of forgery ones. Through using the nonlinear local optimal time warping, together with the linear time warping, the feature space can be divided into several subspaces. Each subspace indicates genuine signatures with different confidence level. This enables the signature verification system to satisfy the requirement of different security.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2002年第10期1227-1232,共6页
Journal of Computer Research and Development
基金
华中科技大学博士后基金资助 ( K- K1 830 0 7)
