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

The authors propose a pattern recognition system which is insensitive to the rotation of the input pattern by various degrees. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. To illustrate the effectiveness of the system, the authors apply it to rotation-invariant coin recognition of 500 yen and 500 won coins. The results of computer simulation show that a neural network approach will be useful in rotation-invariant pattern recognition