Artificial neural network approach to authentication of coins by vision-based minimization

  • Authors:

  • Jang-Ping Wang;Yi-Cih Jheng;Guo-Ming Huang;Jen-Hsien Chien

  • Affiliations:

  • National Taiwan Ocean University, Department of Marine Engineering, 2 Pei-Ning Road, 202-24, Keelung, Taiwan, ROC and National Taiwan Ocean University, Research Centre of Material Processing and M ...;National Taiwan Ocean University, Department of Marine Engineering, 2 Pei-Ning Road, 202-24, Keelung, Taiwan, ROC;National Taiwan Ocean University, Department of Marine Engineering, 2 Pei-Ning Road, 202-24, Keelung, Taiwan, ROC;Asian Coin Certification Authority, 136, Hsi-Ning S.Rd., Taipei, Taiwan, ROC

  • Venue:
  • Machine Vision and Applications
  • Year:
  • 2011

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Abstract

A new inspection system, consisting of two procedures for the authentication of coins, is proposed in this paper. In the first procedure, optimum image-matching positions are found by minimizing the matching error of the test coins with their prototype coins. The second procedure is the decision-making process that inspects the coins as genuine or spurious by the Back-Propagation Neural Network combined with the concept of eigen-section. Unlike the traditional approach based on gray-level values, the quantity (8 bits) of the color’s scale has been adopted. The discrimination results are presented and discussed in this study.