Abstract
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
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