WaveLBP based hierarchical features for image classification

Pattern Recognition Letters

Volumn 34, Issue 12, 2013, Pages 1323-1328

  Song, Tiecheng ^a   Li, Hongliang ^a  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

Gaussian mixture model (GMM); Image classification; Image descriptor; Local binary pattern (LBP); Wavelet decomposition

Indexed keywords

CLASSIFICATION ACCURACY; GAUSSIAN MIXTURE MODEL; HIERARCHICAL FEATURES; IMAGE DESCRIPTIONS; IMAGE DESCRIPTOR; IMAGE REPRESENTATIONS; LOCAL BINARY PATTERNS; VISUAL RECOGNITION;

WAVELET DECOMPOSITION;

IMAGE CLASSIFICATION;

EID: 84878361385     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2013.04.020     Document Type: Article

References (33)

1. T. Ahonen, A. Hadid, and M. Pietikäinen Face description with local binary patterns: application to face recognition IEEE Trans. Pattern Anal. Mach. Intell. 28 12 2006 2037 2041 (Pubitemid 46405714)
2. T. Ahonen, and M. Pietikäinen Image description using joint distribution of filter bank responses Pattern Recogn. Lett. 30 4 2009 368 376
3. J. Beck, A. Sutter, and R. Ivry Spatial frequency channels and perceptual grouping in texture segregation Comput. Vision Graph. Image Process. 37 2 1987 299 325 (Pubitemid 17532325)
4. Bosch, A., Zisserman, A., Munoz, X., 2007. Representing shape with a spatial pyramid kernel. In: ACM International Conference on Image and Video Retrieval, pp. 401-408. (Pubitemid 350229652)
5. Dalal, N., Triggs, B., 2005. Histograms of oriented gradients for human detection. In: IEEE Conference on Computer Vision and, Pattern Recognition, pp. 886-893. (Pubitemid 43897286)
6. Dance, C., Willamowski, J., Fan, L., Bray, C., Csurka, G., 2004. Visual categorization with bags of keypoints. In: ECCV International Workshop on Statistical Learning in Computer Vision.
7. Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L., 2009. Imagenet: a large-scale hierarchical image database. In: IEEE Conference on Computer Vision and, Pattern Recognition, pp. 248-255.
8. Z. 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
9. M. Heikkilä, M. Pietikäinen, and C. Schmid Description of interest regions with local binary patterns Pattern Recogn. 42 3 2009 425 436
10. Huang, X., Li, S., Wang, Y., 2004. Shape localization based on statistical method using extended local binary pattern. In: IEEE First Symposium on Multi-Agent Security and Survivability, pp. 184-187. (Pubitemid 40498060)
11. Hussain, S.U., Triggs, B., 2012. Visual recognition using local quantized patterns. In: European Conference on Computer Vision, pp. 716-729.
12. 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 (Pubitemid 41245056)
13. Lazebnik, S., Schmid, C., Ponce, J., 2006. Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. In: IEEE Conference on Computer Vision and, Pattern Recognition, pp. 2169-2178. (Pubitemid 44931582)
14. H. Li, and K.N. Ngan A co-saliency model of image pairs IEEE Trans. Image Process. 20 12 2011 3365 3375
15. Z. Li, G. Liu, Y. Yang, and J. You Scale- and rotation-invariant local binary pattern using scale-adaptive texton and subuniform-based circular shift IEEE Trans. Image Process. 21 4 2012 2130 2140
16. Liao, S., Chung, A.C.S., 2007. Face recognition by using elongated local binary patterns with average maximum distance gradient magnitude. In: Asian Conference on Computer Vision, pp. 672-679.
17. S. Liao, M. Law, and A. Chung Dominant local binary patterns for texture classification IEEE Trans. Image Process. 18 5 2009 1107 1118
18. D. Lowe Distinctive image features from scale-invariant key-points Int. J. Comput. Vis. 60 2 2004 91 110
19. T. Ojala, M. Pietikäinen, and T. Mäenpää Multiresolution gray-scale and rotation invariant texture classification with local binary patterns IEEE Trans. Pattern Anal. Mach. Intell. 24 7 2002 971 987 (Pubitemid 34835471)
20. A. Oliva, and A. Torralba Modeling the shape of the scene: a holistic representation of the spatial envelope Int. J. Comput. Vis. 42 3 2001 145 175 (Pubitemid 32680801)
21. Perronnin, F., Dance, C., 2007. Fisher kernels on visual vocabularies for image categorization. In: IEEE Conference on Computer Vision and, Pattern Recognition, pp. 1-8.
22. Perronnin, F., Sánchez, J., Mensink, T., 2010. Improving the fisher kernel for large-scale image classification. In: European Conference on Computer Vision, pp. 143-156.
23. Philbin, J., Chum, O., Isard, M., Sivic, J., Zisserman, A., 2008. Lost in quantization: improving particular object retrieval in large scale image databases. In: IEEE Conference on Computer Vision and, Pattern Recognition, pp. 1-8.
24. C. Schmid, and R. Mohr Local grayvalue invariants for image retrieval IEEE Trans. Pattern Anal. Mach. Intell. 19 5 1997 530 535 (Pubitemid 127762247)
25. C. Shan Learning local binary patterns for gender classification on real-world face images Pattern Recogn. Lett. 33 4 2012 431 437
26. Sivic, J., Zisserman, A., 2003. Video google: a text retrieval approach to object matching in videos. In: IEEE International Conference on Computer Vision, pp. 1470-1477.
27. T. Song, and H. Li Local polar DCT features for image description IEEE Signal Process. Lett. 20 1 2013 59 62
28. T. Tuytelaars, and L.V. Gool Matching widely separated views based on affine invariant regions Int. J. Comput. Vis. 59 1 2004 61 85
29. J. Van Gemert, C. Veenman, A. Smeulders, and J. Geusebroek Visual word ambiguity IEEE Trans. Pattern Anal. Mach. Intell. 32 7 2010 1271 1283
30. D. Zhang, M.M. Islam, G. Lu, and I.J. Sumana Rotation invariant curvelet features for region based image retrieval Int. J. Comput. Vis. 98 2 2012 187 201
31. 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 (Pubitemid 46181625)
32. Zhang, W., Shan, S., Gao, W., Chen, X., Zhang, H., 2005. Local Gabor binary pattern histogram sequence (LGBPHS): a novel non-statistical model for face representation and recognition. In: IEEE International Conference on Computer Vision, pp. 786-791. (Pubitemid 44055035)
33. G. Zhao, T. Ahonen, J. Matas, and M. Pietikäinen Rotation-invariant image and video description with local binary pattern features IEEE Trans. Image Process. 21 4 2012 1465 1477