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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 105))

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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

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© 2011 Springer-Verlag Berlin Heidelberg

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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

  • eBook Packages: EngineeringEngineering (R0)

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