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Rotation-invariant neural pattern recognition system with application to coin recognition

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4 Author(s)
Fukumi, M. ; Fac. of Eng., Tokushima Univ., Japan ; Omatu, S. ; Takeda, F. ; Kosaka, T.

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

Published in:

Neural Networks, IEEE Transactions on  (Volume:3 ,  Issue: 2 )

Date of Publication:

Mar 1992

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