摘要
目的为提高在线手写签名认证的速度,提出一种基于频域分析的在线手写签名认证算法,用于在线手写签名认证的粗分类.方法首先使用快速傅立叶变换对在线手写签名原始特征向量进行映射,然后抽取低频信息构成新的特征描述,最后使用加权认证算法实现在线手写签名的认证.结果算法提高了在线手写签名认证的速度,且在SVC2004task2数据集上取得的ERR为10%.结论快速傅立叶变换抽取频域特征易于区分伪造签名,且快速有效.依据用户各种特征稳定程度进行加权认证,提高了系统的鲁棒性.
In order to improve the speed of online hand-written signature authentification, we propose an algorithm based on the analysis of frequency range, for the rough classification of online hand-written signature. Initially, we mapped the characteristic vectors of signatures to frequency range by the Fast Fourier Transform. Then we formed the new characteristic descriptions by extracting the part in low frequency. Finally, we achieved on-line hand-written signature verification with weighted verification algorithm. The algorithm improved the speed of online hand-written signature verification and the experimental result of ERR with the dataset of SCV2004 task 2 was 10 %. The method, extracting frequency range characteristic using fast Fournier transformation, can be easily used to differentiate forge signatures, and it has great advantage in speed and efficiency. According to the stable degree of each kind of characteristics for each user, weighted authentification algorithm enhances the robustness of the system.
出处
《沈阳建筑大学学报（自然科学版）》
EI
CAS
2008年第6期1128-1131,共4页
Journal of Shenyang Jianzhu University：Natural Science
基金
辽宁省自然科学基金项目(20072009)
关键词
在线手写签名认证
快速傅立叶变换
特征抽取
加权认证
on-line hand-written signature verification
fast Fourier transform
characteristic extraction
weighted verification
