Effective texture classification by texton encoding induced statistical features

Pattern Recognition

Volumn 48, Issue 2, 2015, Pages 447-457

  Xie, Jin ^a,b   Zhang, Lei ^a   You, Jane ^a   Shiu, Simon ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b NEW YORK UNIVERSITY ABU DHABI   (United Arab Emirates)

Author keywords

Sparse representation; Texton learning; Texture classification; Texture feature extraction

Indexed keywords

CONCATENATED CODES; ENCODING (SYMBOLS); EXTRACTION; FEATURE EXTRACTION; GRAPHIC METHODS; K-MEANS CLUSTERING; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; SIGNAL ENCODING; TEXTURES;

L1-NORM MINIMIZATIONS; REGULARIZED LEAST SQUARES; SPARSE REPRESENTATION; STATISTICAL FEATURES; SUBSPACE CLASSIFIER; TEXTON LEARNING; TEXTURE CLASSIFICATION; TEXTURE FEATURE EXTRACTION;

CLASSIFICATION (OF INFORMATION);

EID: 84910129220     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2014.08.014     Document Type: Article

References (36)

1. T. Ojala, M. Pietikäinen, and T. Mäenpää Multi-resolution gray-scale and rotation invariant texture classification with local binary patterns IEEE Trans. Pattern Anal. Mach. Intell. 7 24 2002 971 987
2. S. Liao, W.K. Law, and C.S. Chung Dominant local binary pattern for texture classification IEEE Trans. Image Process. 18 5 2009 1107 1118
3. Z.H. Guo, L. Zhang, and D. Zhang A completed modeling of local binary pattern operator for texture classification IEEE Trans. Image Process. 19 6 2010 1657 1663
4. Z.H. Guo, L. Zhang, and D. Zhang Rotation invariant texture classification using LBP variance (LBPV) with global matching Pattern Recognit. 43 3 2010 706 719
5. Y. Xu, X. Yang, H. Ling, H. Ji, A new texture descriptor using multifractal analysis in multi-orientation wavelet pyramid, in: Proceedings of Computer Vision and Pattern Recognition, 2010, pp. 161-168.
6. M. Crosier, and L. Griffin Using basic image features for texture classification Int. J. Comput. Vis. 88 3 2010 447 460
7. T. Leung, and J. Malik Representing and recognizing the visual appearance of materials using three-dimensional textons Int. J. Comput. Vis. 43 1 2001 29 44
8. O.G. Cula, and K.J. Dana 3D texture recognition using bidirectional feature histograms Int. J. Comput. Vis. 59 1 2004 33 60
9. M. Varma, and A. Zisserman A statistical approach to material classification from single images Int. J. Comput. Vis. 62 2 2005 61 81
10. M. Varma, and A. Zisserman A statistical approach to material classification using image patch examplars IEEE Trans. Pattern Anal. Mach. Intell. 31 11 2009 2032 2047
11. S. Lazebnik, C. Schmid, and J. Ponce A sparse texture representation using local affine regions IEEE Trans. Pattern Anal. Mach. Intell. 27 8 2005 1265 1278
12. J. Zhang, M. Marszalek, S. Lazebnik, and C. Schmid Local features and kernels for classification of texture and object categories a comprehensive study Int. J. Comput. Vis. 73 2 2007 213 238
13. L. Liu, P. Fieguth, G.Y. Kuang, H.B. Zha, Sorted random projections for robust texture classification, in: Proceedings of International Conference on Computer Vision, 2011, pp. 391-398.
14. J. Xie, L. Zhang, J. You, D. Zhang, Texture classification via patch-based sparse texton learning, in: Proceedings of International Conference Image Processing, 2010, pp. 2737-2740.
15. A. Beck, and M. Teboulle A fast iterative shrinkage-thresholding algorithm for linear inverse problems SIAM J. Imaging Sci. 2 1 2009 183 202
16. 1 -problems in compressive sensing SIAM J. Sci. Comput. 33 1 2011 250 278
17. K. Dana, B. van Ginneken, S.K. Nayar, and J.J. Koenderink Reflectance and texture of real world surfaces ACM Trans. Gr. 18 1 1999 1 34
18. E. Hayman, B. Caputo, M. Fritz, J. O. Eklundh, On the significance of real-world conditions for material classification, in: Proceedings of European Conference Computer Vision, 2004, pp. 253-266.
19. D. Lowe Distinctive image features from scale-invariant features Int. J. Comput. Vis. 60 2 2004 91 110
20. M. Varma, R. Garg, Locally invariant fractal features for statistical texture classification, in: Proceedings of International Conference Computer Vision, 2007, pp. 1-8.
21. Y. Xu, H. Ji, and C. Fermuller Viewpoint invariant texture description using fractal analysis Int. J. Comput. Vis. 83 1 2009 85 100
22. M. Varma, A. Zisserman, Classifying images of materials: achieving viewpoint and illumination independence, in: Proceedings of European Conference Computer Vision, 2002, pp. 255-271.
23. M. Varma, A. Zisserman, Texture classification: are filter banks necessary? in: Proceedings of Computer Vision and Pattern Recognition, 2003, pp. 691-698.
24. K. Skretting, J.H. Husøy, Texture classification using sparse frame based representations, EURASIP J. Appl. Signal Process. (2006).
25. J. Mairal, F. Bach, J. Ponce, G. Sapiro, A. Zisserman, Discriminative learned dictionaries for local image analysis, in: Proceedings of Computer Vision and Pattern Recognition, 2008, pp. 1-8.
26. K. Tanabe Conjugate-gradient method for computing the Moore-Penrose inverse and rank of a matrix J. Optim. Theory Appl. 22 1 1977 1 23
27. W. Johnson, J. Lindenstrauss, Extensions of Lipschitz mappings into a Hilbert space, in: Proceedings of Conference in Modern Analysis and Probability, 1984, vol. 2006, pp. 1-11.
28. F. Bianconi, A. Fernández, A unifying framework for LBP and related methods, in: Local Binary Patterns: New Variants and Applications (Studies in Computational Intelligence), Springer, 2014, pp. 17-46.
29. N.P. Doshi, G. Schaefer, Dominant multi-dimensional local binary patterns, in: Proceedings of Conference on Signal Processing, Communications and Computing, 2013, pp. 1-6.
30. M.J. Gangeh, A. Ghodsi, M.S. Kamel, Dictionary learning in texture classification, in: Proceedings of Conference on Image Analysis and Recognition, 2011, pp. 335-343.
31. J. van Gemert, C.J. Veenman, A.W.M. Smeulders, J.M. Geusebroek, Visual word ambiguity, IEEE Trans. Pattern Anal. Mach. Intell. 32(7) (2010) 1271-1283.
32. Y. Guo, G. Zhao, and M. Pietikäinen Discriminant features for texture description Pattern Recognit. 45 10 2012 3825 3843
33. L. Liu, L. Wang, X. Liu, In defense of soft-assignment coding, in: Proceedings of International Conference on Computer Vision, 2011, pp. 2486-2493.
34. L. Nanni, A. Lumini, and S. Brahnam Local binary patterns variants as texture descriptors for medical image analysis Artif. Intell. Med. 49 2 2010 117 125
35. J.F. Ren, X.D. Jiang, and J.S. Yuan Noise-resistant local binary pattern with an embedded error-correction mechanism IEEE Trans. Image Process. 22 10 2013 4049 4060
36. A. Satpathy, X.D. Jiang, and H.L. Eng LBP based edge-texture features for object recognition IEEE Trans. Image Process. 23 5 2014 1953 1964