Comparison of edge detectors: a methodology and initial study
Computer Vision and Image Understanding
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution Color Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Classification of coins using an eigenspace approach
Pattern Recognition Letters
Image based recognition of ancient coins
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Neural networks for classification: a survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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IEEE Transactions on Image Processing
Histogram-based segmentation in a perceptually uniform color space
IEEE Transactions on Image Processing
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Illegal trade and theft of coins appears to be a major part of the illegal antiques market. Image based recognition of coins could substantially contribute to fight against it. Central component in the permanent identification and traceability of coins is the underlying classification and identification technology. However, currently available algorithms focus basically on the recognition of modern coins. To date, no optical recognition system for ancient coins has been researched successfully. In this paper, we give an overview over the challenges faced by optical recognition algorithms. Furthermore, we show that image based recognition can assist the manual process of coin classification and identification by restricting the range of possible coins of interest.