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

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.

Key words: signature verification, hierarchical classifying, extreme learning machine, sparse representations classifier, static features, pseudo-dynamic features