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An Application of Rough Sets and Haar Wavelets to Face Recognition

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Rough Sets and Current Trends in Computing (RSCTC 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2005))

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Abstract

The paper presents an application of data mining methods for face recognition. The proposed methods are based on wavelets, principal components analysis, rough sets and neural networks. The features from the face images have been extracted based on the Haar wavelets followed by the principal component analysis (PCA), and rough sets processing. We have applied the rough sets methods for selection of facial features based on the minimum concept description paradigm. The recognition of facial images, for the reduced features, has been carried on using error backpropagation neural network.

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References

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Author information

Authors and Affiliations

  1. Department of Mathematical and Computer Sciences, San Diego State University, CA 92182, San Diego, USA

    R. Swiniarski

Authors
  1. R. Swiniarski
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Regina Regina, S4S 0A2, Saskatchewan, Canada

    Wojciech Ziarko  & Yiyu Yao  & 

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© 2001 Springer-Verlag Berlin Heidelberg

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Swiniarski, R. (2001). An Application of Rough Sets and Haar Wavelets to Face Recognition. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X_70

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  • DOI: https://doi.org/10.1007/3-540-45554-X_70

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43074-2

  • Online ISBN: 978-3-540-45554-7

  • eBook Packages: Springer Book Archive

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