Classification of coins using an eigenspace approach
Pattern Recognition Letters
Stand-alone embedded vision system based on fuzzy associative database
Image and Vision Computing
On ancient coin classification
VAST'07 Proceedings of the 8th International conference on Virtual Reality, Archaeology and Intelligent Cultural Heritage
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In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition