Modification of correlation kernels in SVM, KPCA and KCCA in texture classification

Modified versions of the correlation kernels in the kernel methods, e.g., SVMs, kPCA and kCCA are presented, which are based on the L/sub p/ norm and max norm as well as the blindness of the odd-order autocorrelations to sinusoidal or symmetrically distributed signals. The poor generalization of the higher-order correlation kernels and the inferior performance of the correlation kernels of odd-orders to even-orders are improved with the modifications. The performance of the modified correlation kernels is evaluated and compared in texture classification experiments.

[1]  Samy Bengio,et al.  SVMTorch: Support Vector Machines for Large-Scale Regression Problems , 2001, J. Mach. Learn. Res..

[2]  Bernhard Schölkopf,et al.  Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.

[3]  Horst Bischof,et al.  Appearance models based on kernel canonical correlation analysis , 2003, Pattern Recognit..

[4]  Pedro E. López-de-Teruel,et al.  Nonlinear kernel-based statistical pattern analysis , 2001, IEEE Trans. Neural Networks.

[5]  John Shawe-Taylor,et al.  Canonical Correlation Analysis: An Overview with Application to Learning Methods , 2004, Neural Computation.

[6]  Malte Kuss,et al.  The Geometry Of Kernel Canonical Correlation Analysis , 2003 .

[7]  Phil Brodatz,et al.  Textures: A Photographic Album for Artists and Designers , 1966 .

[8]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[9]  Yo Horikawa,et al.  Use of Autocorrelation Kernels in Kernel Canonical Correlation Analysis for Texture Classification , 2004, ICONIP.

[10]  Jean-Philippe Thiran,et al.  Pattern recognition using higher-order local autocorrelation coefficients , 2004, Pattern Recognit. Lett..

[11]  John A. McLaughlin,et al.  Nth-Order Autocorrelations in Pattern Recognition , 1968, Inf. Control..

[12]  Hang Joon Kim,et al.  Support Vector Machines for Texture Classification , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  A. Lohmann,et al.  Triple correlations , 1984, Proceedings of the IEEE.

[14]  Trygve Randen,et al.  Filtering for Texture Classification: A Comparative Study , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Jean-Philippe Thiran,et al.  Higher order autocorrelations for pattern classification , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[16]  Gunnar Rätsch,et al.  An introduction to kernel-based learning algorithms , 2001, IEEE Trans. Neural Networks.

[17]  Yo Horikawa.  Comparison of support vector machines with autocorrelation kernels for invariant texture classification , 2004, ICPR 2004.

[18]  H. J. Kim,et al.  Kernel principal component analysis for texture classification , 2001, IEEE Signal Processing Letters.