A new method for image segmentation
Computer Vision, Graphics, and Image Processing
Evaluation of Binarization Methods for Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Quantum computation and quantum information
Quantum computation and quantum information
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Shape Matching: Similarity Measures and Algorithms
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Classification of coins using an eigenspace approach
Pattern Recognition Letters
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image based recognition of ancient coins
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Rotation-invariant neural pattern recognition system with application to coin recognition
IEEE Transactions on Neural Networks
Recognizing Ancient Coins Based on Local Features
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Numismatic Object Identification Using Fusion of Shape and Local Descriptors
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
On the use of computer vision for numismatic research
VAST'08 Proceedings of the 9th International conference on Virtual Reality, Archaeology and Cultural Heritage
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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. The first step of a computer aided system is the segmentation of the coin in the image. Next, a feature extraction process measures the coin in order to describe the coin unambiguously. In this paper, we focus on the segmentation task, followed by a comparison of features relevant for coin classification. Results of the algorithms implemented are presented for an image database of ancient coins.