Machine Vision and Applications

, Volume 22, Issue 6, pp 983–994 | Cite as

Identification of ancient coins based on fusion of shape and local features

  • Reinhold Huber-Mörk
  • Sebastian Zambanini
  • Maia Zaharieva
  • Martin Kampel
Original Paper

Abstract

We present a vision-based approach to ancient coins’ identification. The approach is a two-stage procedure. In the first stage an invariant shape description of the coin edge is computed and matching based on shape is performed. The second stage uses preselection by the first stage in order to refine the matching using local descriptors. Results for different descriptors and coin sides are combined using naive Bayesian fusion. Identification rates on a comprehensive data set of 2400 images of ancient coins are on the order of magnitude of 99%.

Keywords

Coin identification Ancient coins Shape matching Local features Fusion 

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Reinhold Huber-Mörk
    • 1
  • Sebastian Zambanini
    • 2
  • Maia Zaharieva
    • 3
  • Martin Kampel
    • 2
  1. 1.Business Unit High Performance Image Processing, Department Safety & SecurityAustrian Institute of Technology GmbHSeibersdorfAustria
  2. 2.Computer Vision Lab, Institute of Computer-Aided AutomationVienna University of TechnologyViennaAustria
  3. 3.Interactive Media Systems Group, Institute of Software Technology and Interactive SystemsVienna University of TechnologyViennaAustria

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