Abstract

We propose a training algorithm for one-class classifiers in order to minimize the classification error. The aim is to choose the optimal value of the slack parameter, which controls the selectiveness of a classifier. The one-class classifier based on the coordinated clusters representation of images is trained and then used for the classification of texture images. As the slack parameter C varies through a range of values, for each C, the misclassification rate is computed using only the training samples. The value of C that yields the minimum misclassification rate, estimated over the training set, is taken as the optimal value, Copt. Finally, the optimized classifier is tested on the extended database of images. Experimental results demonstrate the validity of the proposed method. In our experiments, classification efficiency approaches, or is equal to, 100%, after the optimal training of the classifier.

© 2008 Optical Society of America

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  1. K. Song, J. Kittler, and M. Petrou, "Defect detection in random color textures," Image Vis. Comput. 14, 667-683 (1996).
  2. F. Lumbreras, R. Baldrich, M. Vanrell, J. Serrat, and J. J. Villanueva, "Multiresolution color texture classification of ceramic tiles," in Recent Research Developments in Optical Engineering (Research Signpost, 1999), Vol. 2, pp. 213-228.
  3. M. L. Smith and R. J. Stamp, "Automated inspection of textured ceramic tiles," Comput. Ind. 43, 73-82 (2000).
  4. G. Paschos, "Fast color texture recognition using chromaticity moments," Pattern Recogn. Lett. 21, 837-841 (2000).
  5. S. Kukkonen, H. Kälviäinen, and J. Parkkinen, "Color features for quality control in ceramic tile industry," Opt. Eng. 40, 170-177 (2001).
  6. R. O. Duda, P. E. Hart, and D. G. Stork, "Pattern Classification," 2nd ed. (Wiley, 2001).
  7. M. Unser, "A fast texturé classifier based on cross entropy minimization," in Proceedings of the EUSIPCO'83 (North-Holland, 1983), pp. 261-264.
  8. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. (Academic, 1990).
  9. K. Irahama and Y. Furukawa, "Gradient descent learning of nearest neighbor classifiers with outlier rejection," Pattern Recogn. 28, 761-768 (1995).
  10. M. M. Moya and D. R. Hush, "Network constraints and multi-objective optimization for one-class classification," Neural Networks 9, 463-474 (1996).
  11. D. M. J. Tax and R. P. W. Duin, "Support vector domain description," Pattern Recogn. Lett. 20, 1191-1199 (1999).
  12. D. M. J. Tax, "One-class classification: concept-learning in the absence of counterexamples," Ph.D. dissertation (Delft University of Technology, 2001).
  13. D. M. J. Tax and R. P. W. Duin, "Uniform object generation for optimizing one-class classifiers," J. Mach. Learn. Res. 2, 155-173 (2002).
  14. P. Juszczak, "Learning to recognize: a study on one-class classification and active learning," Ph.D. dissertation (Delft University of Technology, 2006).
  15. R. E. Sánchez-Yáñez, E. V. Kurmyshev, and F. J. Cuevas, "A framework for texture classification using the coordinated clusters representation," Pattern Recogn. Lett. 24, 21-31 (2003).
  16. R. E. Sánchez-Yáñez, E. V. Kurmyshev, and A. Fernández, "One-class texture classifier in the CCR feature space," Pattern Recogn. Lett. 24, 1503-1511 (2003).
  17. E. V. Kurmyshȩv and R. E. Sánchez-Yáñez, "Comparative experiment with colour texture classifier using the CCR feature space," Pattern Recogn. Lett. 26, 1346-1353 (2005).
  18. E. V. Kurmyshev, M. Poterasu, and J. T. Guillen-Bonilla, "Image scale determination for optimal texture classification using coordinated clusters representation," Appl. Opt. 46, 1467-1476 (2007).
  19. J. T. Guillen-Bonilla, E. Kurmyshev, and A. Fernández, "Quantifying a similarity of classes of texture images," Appl. Opt. 46, 5562-5570 (2007).
  20. E. V. Kurmyshev, "Classification of texture images using coordinated clusters representation, in Recent Advances in Optical Metrology (Research Signpost, 2007), pp. 155-226.
  21. A. M. Molinaro, R. Simon, and R. M. Pfeiffer, "Prediction error estimation: a comparison of resampling methods," Bioinformatics 21, 3301-3307 (2005).
  22. OuTex, Texture Database, http://www.outex.oulu.fi/temp/.

2007 (2)

2005 (2)

E. V. Kurmyshȩv and R. E. Sánchez-Yáñez, "Comparative experiment with colour texture classifier using the CCR feature space," Pattern Recogn. Lett. 26, 1346-1353 (2005).

A. M. Molinaro, R. Simon, and R. M. Pfeiffer, "Prediction error estimation: a comparison of resampling methods," Bioinformatics 21, 3301-3307 (2005).

2003 (2)

R. E. Sánchez-Yáñez, E. V. Kurmyshev, and F. J. Cuevas, "A framework for texture classification using the coordinated clusters representation," Pattern Recogn. Lett. 24, 21-31 (2003).

R. E. Sánchez-Yáñez, E. V. Kurmyshev, and A. Fernández, "One-class texture classifier in the CCR feature space," Pattern Recogn. Lett. 24, 1503-1511 (2003).

2002 (1)

D. M. J. Tax and R. P. W. Duin, "Uniform object generation for optimizing one-class classifiers," J. Mach. Learn. Res. 2, 155-173 (2002).

2001 (1)

S. Kukkonen, H. Kälviäinen, and J. Parkkinen, "Color features for quality control in ceramic tile industry," Opt. Eng. 40, 170-177 (2001).

2000 (2)

M. L. Smith and R. J. Stamp, "Automated inspection of textured ceramic tiles," Comput. Ind. 43, 73-82 (2000).

G. Paschos, "Fast color texture recognition using chromaticity moments," Pattern Recogn. Lett. 21, 837-841 (2000).

1999 (1)

D. M. J. Tax and R. P. W. Duin, "Support vector domain description," Pattern Recogn. Lett. 20, 1191-1199 (1999).

1996 (2)

K. Song, J. Kittler, and M. Petrou, "Defect detection in random color textures," Image Vis. Comput. 14, 667-683 (1996).

M. M. Moya and D. R. Hush, "Network constraints and multi-objective optimization for one-class classification," Neural Networks 9, 463-474 (1996).

1995 (1)

K. Irahama and Y. Furukawa, "Gradient descent learning of nearest neighbor classifiers with outlier rejection," Pattern Recogn. 28, 761-768 (1995).

Appl. Opt. (2)

Bioinformatics (1)

A. M. Molinaro, R. Simon, and R. M. Pfeiffer, "Prediction error estimation: a comparison of resampling methods," Bioinformatics 21, 3301-3307 (2005).

Comput. Ind. (1)

M. L. Smith and R. J. Stamp, "Automated inspection of textured ceramic tiles," Comput. Ind. 43, 73-82 (2000).

Image Vis. Comput. (1)

K. Song, J. Kittler, and M. Petrou, "Defect detection in random color textures," Image Vis. Comput. 14, 667-683 (1996).

J. Mach. Learn. Res. (1)

D. M. J. Tax and R. P. W. Duin, "Uniform object generation for optimizing one-class classifiers," J. Mach. Learn. Res. 2, 155-173 (2002).

Neural Networks (1)

M. M. Moya and D. R. Hush, "Network constraints and multi-objective optimization for one-class classification," Neural Networks 9, 463-474 (1996).

Opt. Eng. (1)

S. Kukkonen, H. Kälviäinen, and J. Parkkinen, "Color features for quality control in ceramic tile industry," Opt. Eng. 40, 170-177 (2001).

Pattern Recogn. (1)

K. Irahama and Y. Furukawa, "Gradient descent learning of nearest neighbor classifiers with outlier rejection," Pattern Recogn. 28, 761-768 (1995).

Pattern Recogn. Lett. (5)

G. Paschos, "Fast color texture recognition using chromaticity moments," Pattern Recogn. Lett. 21, 837-841 (2000).

D. M. J. Tax and R. P. W. Duin, "Support vector domain description," Pattern Recogn. Lett. 20, 1191-1199 (1999).

R. E. Sánchez-Yáñez, E. V. Kurmyshev, and F. J. Cuevas, "A framework for texture classification using the coordinated clusters representation," Pattern Recogn. Lett. 24, 21-31 (2003).

R. E. Sánchez-Yáñez, E. V. Kurmyshev, and A. Fernández, "One-class texture classifier in the CCR feature space," Pattern Recogn. Lett. 24, 1503-1511 (2003).

E. V. Kurmyshȩv and R. E. Sánchez-Yáñez, "Comparative experiment with colour texture classifier using the CCR feature space," Pattern Recogn. Lett. 26, 1346-1353 (2005).

Other (8)

E. V. Kurmyshev, "Classification of texture images using coordinated clusters representation, in Recent Advances in Optical Metrology (Research Signpost, 2007), pp. 155-226.

D. M. J. Tax, "One-class classification: concept-learning in the absence of counterexamples," Ph.D. dissertation (Delft University of Technology, 2001).

P. Juszczak, "Learning to recognize: a study on one-class classification and active learning," Ph.D. dissertation (Delft University of Technology, 2006).

F. Lumbreras, R. Baldrich, M. Vanrell, J. Serrat, and J. J. Villanueva, "Multiresolution color texture classification of ceramic tiles," in Recent Research Developments in Optical Engineering (Research Signpost, 1999), Vol. 2, pp. 213-228.

R. O. Duda, P. E. Hart, and D. G. Stork, "Pattern Classification," 2nd ed. (Wiley, 2001).

M. Unser, "A fast texturé classifier based on cross entropy minimization," in Proceedings of the EUSIPCO'83 (North-Holland, 1983), pp. 261-264.

K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. (Academic, 1990).

OuTex, Texture Database, http://www.outex.oulu.fi/temp/.

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