Comparison of support vector machines with autocorrelation kernels for invariant texture classification

Proceedings - International Conference on Pattern Recognition

Volumn 1, Issue , 2004, Pages 660-663

  Horikawa, Yo ^a  

^a KAGAWA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; FOURIER TRANSFORMS; FUNCTIONS; GAUSSIAN NOISE (ELECTRONIC); KALMAN FILTERING; MATHEMATICAL TRANSFORMATIONS; OPTIMIZATION; TEXTURES;

AUTOCORRELATION KERNELS; SUPPORT VECTOR MACHINES (SVM); TEXTURE CLASSIFICATION; TEXTURE IMAGES;

PATTERN RECOGNITION;

EID: 10044249123     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/icpr.2004.1334253     Document Type: Conference Paper

References (14)

1. J. Zhang and T. Tan, "Brief Review of Invariant Texture Analysis Methods", Pattern Recognition, 35, 2002, pp. 735-747.
2. C. Cortes and V. Vapnik, "Support Vector Networks", Machine Learning, 20, 1995, pp. 273-297.
3. K. R. Müller, et al., "An Introduction to Kernel-Based Learning Algorithms", IEEE Trans. Neural Networks, 12, 2001, pp. 181-201.
4. K. I. Kim, et al., "Support Vector Machines for Texture Classification", IEEE Trans. Pattern Analysis and Machine Intelligence, 24, 2002, pp. 1542-1550.
5. V. Popovici and J. P. Thiran, "Higher Order Autocorrelations for Pattern Classification", Proc. IEEE 2001 International Conference on Image Processing (ICIP 2001), 2001, pp. 724-727.
6. J. A. McLaughlin and J. Raviv, "Nth-Order Autocorrelations in Pattern Recognition", Information and Control, 12, 1968, pp. 121-142.
7. Y. Horikawa, "Pattern Recognition with Invariance to Similarity Transformations Based on the Third-Order Correlation", Proc. 13th International Conference on Pattern Recognition (ICPR '96), 2, 1996, pp. 200-204.
8. V. Murino, et al., "Noisy Texture Classification: A Higher-Order Statistics Approach", Pattern Recognition, 31, 1998, pp. 383-393.
9. Y. Horikawa, "Bispectrum-Based Feature of 2D and 3D Images Invariant to Similarity Transformations", Proc. 15th International Conference on Pattern Recognition (ICPR 2000), 2, 2000, pp. 511-514.
10. Y. Horikawa, "Invariant Noisy Texture Classification with Bispectrum-Based Features from Projections", Proc. IEEE 2001 Int. Conf. on Image Processing (ICIP 2001), 2001, pp. 606-609.
11. The Vision Texture, http://www-white.media.mit.edu/vismod/imagery/ VisionTexture/vistex.html
12. P. Brodatz, Textures: A Photographic Album for Artists and Designers, Dover, New York, 1966.
13. T. Randen and J. H. Husøy, "Filtering for Texture Classification: A Comparative Study", IEEE Trans. Pattern Analysis and Machine Intelligence, 21, 1999, pp. 291-310.
14. R. Collobert and S. Bengio, "SVMTorch: Support Vector Machines for Large-Scale Regression Problems", J. Machine Learning Research, 1, 2001, pp. 143-160.