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Metallic Coin Analyzer System For Automatic Identification And Classification


  • Stefan Nicolae Tica

    () ("Politehnica" University of Bucharest)

  • Costin-Anton Boiangiu

    () ("Politehnica" University of Bucharest)

  • Ion Bucur

    () ("Politehnica" University of Bucharest)


In this paper, we would like to present and discuss a system that automatically classifies coins. This flexible system can identify coins having different features and being photographed in different light conditions. For this purpose, a set of strong techniques for thresholding, edge detection and frequency transform were used in order to generate a fingerprint as meaningful and as invariant as possible for every coin class. Usually, the capturing of digital images cannot be performed in best conditions and inconsistencies can arise due to various lighting conditions as well as the performance of the capturing device. This article is here to suggest a method to reduce problems generated by lighting, so that image characteristics are more accurate. The proposed solution improves an existing automatic coin classification algorithm by applying illumination correction before the actual classification.

Suggested Citation

  • Stefan Nicolae Tica & Costin-Anton Boiangiu & Ion Bucur, 2015. "Metallic Coin Analyzer System For Automatic Identification And Classification," Romanian Economic Business Review, Romanian-American University, vol. 9(2), pages 291-308, December.
  • Handle: RePEc:rau:journl:v:10:y:2015:i:2:p:291-308

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    References listed on IDEAS

    1. Mihai Zaharescu & IonuĊ£ Cosmin Petrescu, 2013. "Edge Detection In Document Analysis," Romanian Economic Business Review, Romanian-American University, vol. 7(1), pages 156-165, May.
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