DocumentCode
856645
Title
Rotation-invariant neural pattern recognition system with application to coin recognition
Author
Fukumi, Minoru ; Omatu, Sigeru ; Takeda, Fumiaki ; Kosaka, Toshihisa
Author_Institution
Fac. of Eng., Tokushima Univ., Japan
Volume
3
Issue
2
fYear
1992
fDate
3/1/1992 12:00:00 AM
Firstpage
272
Lastpage
279
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
Keywords
computerised pattern recognition; neural nets; 500 won coin; 500 yen coin; coin recognition; computerised pattern recognition; fixed invariance network; rotation-invariant neural pattern recognition system; trainable multilayered network; Associate members; Data preprocessing; Explosions; Fourier transforms; Neural networks; Neurons; Pattern matching; Pattern recognition; Resonance; Slabs;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.125868
Filename
125868
Link To Document