Abstract
Up to now, much research of the application to neural networks (NN) has been reported. We have proposed a neuro-pattern recognition for bill money with masks and have reported its effectiveness for money recognition. Recently, genetic algorithm (GA) is reported as the effective optimizing method. In this paper, we adopt the GA to mask optimization in the recognition method. Namely, we regard the position of the masked part in the input image as a gene. We operate crossover, selection, and mutation to some genes. By repeating a series of these operations, we can get effective masks for paper currency recognition. We compare the ability of NN using the optimized masks by the GA with the one of NN using the random masks determined by random numbers. Then we show that the GA is effective to optimize masks for the method of neuro-pattern recognition with masks. Furthermore, we develop high-speed neuro-recognition board to realize the neuro-pattern recognition for paper currency in the commercial products.
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Reference
F.Takeda, S.Omatu, T.Inoue, and S.Onami, “High Speed Conveyed Bill Money Recognition with Neural Network”, Proceedings of the IMACS/SCINE International Symposium on Robotics, Mechatronics and Manufacturing Systems '92 Kobe, Japan, Vol.1, pp. 16–20, 1992.
F.Takeda, S.Omatu, T.Inoue, and S.Onami, “A Structure Reduction of Neural Network with Random Masks and Bill Money Recognition”, Proceedings of the 2nd International Conference on Fuzzy Logic and Neural Networks, IIZUKA, Japan, Vol.2,pp.809–813, 1992.
F.Takeda and S.Omatu, “Bank Note Recognition System Using Neural Network with Random Masks”, Proceedings of the World Congress on Neural Networks, Portland, USA, Vol.1, pp.241–244, 1993.
F.Takeda and S.Omatu, “Recognition System of US Dollars Using a Neural Network with Random Masks”, Proceedings of the International Joint Conference on Neural Networks, Nagoya, Japan, Vol.2, pp.2033–2036, 1993.
B.Widrow, R.G.Winter, and R.A.Baxter, “Layered Neural Nets for Pattern Recognition”, IEEE Trans. on Acoust., Speech & Signal Process., Vol.36, No.7, pp. 1109–1118, 1988.
D.E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, New York, 1989.
F.Takeda, S.Omatu, S.Onami, T.Kadono, and K.Terada, “A Paper Currency Recognition Method by a Small Size Neural Network with Optimized Masks by GA”, Proceedings of IEEE World Congress on Computational Intelligence, Orlando, USA, Vol.7, pp.4243–4246 1994.
F.Takeda, S.Omatu, S.Onami, T.Kadono, and K.Terada, “A Paper Currency Recognition Method by a Neural Network Using Maks and Mask Optimization by GA,” Proceedings of World Wisemen /women Workshop On Fuzzy Logic And Neural Networks /Genetic Algorithms of IEEE / Nagoya University, Nagoya, Japan 1994.
Kitano,Genetic Algorithm, Sangyo Tosyo, pp.44–60, 1993 (in Japanese)
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© 1995 Springer-Verlag Berlin Heidelberg
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Takeda, F., Omatu, S. (1995). A neuro-money recognition using optimized masks by GA. In: Furuhashi, T. (eds) Advances in Fuzzy Logic, Neural Networks and Genetic Algorithms. WWW 1994. Lecture Notes in Computer Science, vol 1011. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60607-6_13
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DOI: https://doi.org/10.1007/3-540-60607-6_13
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