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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© 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
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