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Texture classification with kernel principal component analysis

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4 Author(s)
Kim, K.I. ; Dept. of Comput. Eng., Kyungpook Nat. Univ., Taegu, South Korea ; Jung, K. ; Park, S.H. ; Kim, H.J.

Kernel principal component analysis (PCA) is presented as a mechanism for extracting textural information. Using the polynomial kernel, higher order correlations of input pixels can be easily used as features for classification. As a result, supervised texture classification can be performed using a neural network

Published in:

Electronics Letters  (Volume:36 ,  Issue: 12 )

Date of Publication:

8 Jun 2000

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