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identification and verification of handwritten signatures using digital image processing techniques in an offline setting

  • Unique Paper ID: 166690
  • Volume: 11
  • Issue: 2
  • PageNo: 1627-1637
  • Abstract:
  • This study provides a writer-independent signature verification system. To classify the data, the system uses K-Nearest Neighbours (KNN) while Fourier Descriptors (FD) are used for feature extraction. In this case, to obtain reliable and steady features we were gathering, scanning and preparing signatures of ten people. As for the performance of the system, it achieved a 95% recognition rate on both the local and MCYT datasets where K=1. There is a need to develop something in this regards because it was shown that the misclassifications were due to having different signature limits. The findings reveal that both FD and KNN function well in writer independent model and provide a reliable solution to the problem of automated signature verification.
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  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 2
  • PageNo: 1627-1637

identification and verification of handwritten signatures using digital image processing techniques in an offline setting

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