A novel data fusion scheme for offline chinese signature verification

  • Authors:
  • Wen-ming Zuo;Ming Qi

  • Affiliations:
  • School of Electronic Business, South China University of Technology, Guangzhou, P.R. China;School of Electronic Business, South China University of Technology, Guangzhou, P.R. China

  • Venue:
  • ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
  • Year:
  • 2005

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Abstract

A novel data fusion signature verification scheme which combines two schemes is proposed. The first scheme with static features described with Pseudo-Zernike invariant moments and some dynamic features is built with a BP (back-propagation) network. In another scheme, 40 values computed with SVD(singular value decomposition) on thinned signature image and thinned high-density image compose the feature vector and another BP network is built for every kind of signature. Then these two BP networks are connected and their outputs are competitively selected to achieve the final output result. A collection of 290 signatures is used to test the verification system. And experiment shows that FAR (False Acceptance Rate) and FRR (False Rejection Rate) can achieve 5.71% and 6.25% respectively.