title: Rotation-invariant neural pattern recognition system with application to coin recognition.
abstract: 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.
authors.affiliation: Fac. of Eng., Tokushima Univ.
authors.forename: M
authors.initials: M
authors.lastname: Fukumi
authors.forename: S
authors.initials: S
authors.lastname: Omatu
authors.forename: F
authors.initials: F
authors.lastname: Takeda
authors.forename: T
authors.initials: T
authors.lastname: Kosaka