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

Content Provider	Springer Nature Link
Author	Huber Mörk, Reinhold Zambanini, Sebastian Zaharieva, Maia Kampel, Martin
Copyright Year	2010
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%.
Starting Page	983
Ending Page	994
Page Count	12
File Format	PDF
ISSN	09328092
Journal	Machine Vision and Applications
Volume Number	22
Issue Number	6
e-ISSN	14321769
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-07-11
Publisher Place	Berlin/Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Coin identification Ancient coins Shape matching Local features Fusion Pattern Recognition Image Processing and Computer Vision Communications Engineering, Networks
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Computer Science Applications Software Hardware and Architecture

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