计算机工程与应用2018，Vol.54Issue(8)：112-118,7.DOI:10.3778/j.issn.1002-8331.1611-0238
层次化分类的离线中文签名真伪鉴别方法
Off-line Chinese handwriting signature verification with hierarchical classification
摘要
Abstract
This paper proposes a hierarchical classification method for Chinese handwriting signature verification called HCSV(Hierarchical Classifier for Signature Verification,HCSV),which combines Extreme Learning Machine(ELM)with Sparse Representation(SR). First of all, taking advantage of the generalization ability and robustness of ELM, random forged signatures which can easily be identified are distinguished.Afterwards,the premeditated forged signatures are selected from the real signatures by sparse representation classifiers which have good ability of feature description.Experimental results show that the proposed method achieves 95.53% verification accuracy,which is better than two state-of-art methods.关键词
签名真伪鉴别/层次化分类/极限学习机/稀疏表示分类/静态特征/伪动态特征Key words
signature verification/hierarchical classifying/extreme learning machine/sparse representations classifier/static features/pseudo-dynamic features分类
信息技术与安全科学引用本文复制引用
魏佳敏,冯筠,卜起荣,高原,赵妍..层次化分类的离线中文签名真伪鉴别方法[J].计算机工程与应用,2018,54(8):112-118,7.基金项目
陕西省教育厅2015年科学研究计划项目(No.15JK1689).本文由陕西省天地网技术重点实验室开放课题基金资助完成. （No.15JK1689）
