Publication: Control chart pattern classification using Fourier descriptors and neural networks
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Issued Date
2011-10-03
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2-s2.0-80053246755
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Mahidol University
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SCOPUS
Bibliographic Citation
2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011 - Proceedings. (2011), 4587-4590
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Pisit Phokharatkul, Supachai Phaiboon Control chart pattern classification using Fourier descriptors and neural networks. 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011 - Proceedings. (2011), 4587-4590. doi:10.1109/AIMSEC.2011.6011169 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/11651
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Control chart pattern classification using Fourier descriptors and neural networks
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Abstract
This paper presents the method of Fourier descriptors and neural networks developed for control chart pattern analysis. The pattern analysis is important to achieve appropriate control and to produce high quality products. This paper also investigates the use of features extracted from Fourier descriptors as the Fourier coefficient components. The Fourier coefficients used to train the neural networks for classifying patterns. Thus, the networks were able to identify the classes. This research concluded the extracted features to improve the performance of the number of Fourier coefficients for neural network training. Experimental results and comparisons based on simulated and unknown data show that the proposed approach performs better than the symbol-sequence histogram with neural network approach. © 2011 IEEE.