Abstract
Structure and properties of fuzzy ART were described. Choice and match function were presented. In order to extracted face feature, low pass filter, cutting minimum intensity and generating vector histogram were used. Fuzzy ART used the vector histogram as the original input vector data to recognize face feature. when the fuzzy ART network parameters were selected properly, simulation experiments showed that maximum online recognition rate was 90.3% and offline recognition rate was nearly 100%.
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References
Li, W.-J., et al.: A Survey of Face Recognition. Pattern Recognition and Artificial Intelligence 19, 58 (2006)
Patra, P.K., Nayak, M., Nayak, S.K., Gobbak, N.K.: Probabilistic neural network for pattern classification. In: IEEE IJCNN, p. 1200 (May 2002)
Picton, P.: Neural Network, Palgrave (2000)
Carpenter, G.A., Grossberg, S.: Fuzzy ARTMAP: A Neural Network Architecture for Incremental Supervised Learning of Analog Multidimensional Map. IEEE Transactions on Neural Networks 3(5) (September 1992)
Kotani, K., Qiu, C., Ohmi, T.: Face Recognition Using Vector Quantization Histogram Metho. In: IEEE ICIP, p. 105 (September 2002)
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Gu, M. (2011). Design and Realizing of Face Recognition Algorithm. In: Jin, D., Lin, S. (eds) Advances in Computer Science, Intelligent System and Environment. Advances in Intelligent and Soft Computing, vol 105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23756-0_43
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DOI: https://doi.org/10.1007/978-3-642-23756-0_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23755-3
Online ISBN: 978-3-642-23756-0
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