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http://dx.doi.org/10.3837/tiis.2014.07.011

Texture superpixels merging by color-texture histograms for color image segmentation  

Sima, Haifeng (School of Computer Science and Technology, Beijing Institute of Technology)
Guo, Ping (School of Computer Science and Technology, Beijing Institute of Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.8, no.7, 2014 , pp. 2400-2419 More about this Journal
Abstract
Pre-segmented pixels can reduce the difficulty of segmentation and promote the segmentation performance. This paper proposes a novel segmentation method based on merging texture superpixels by computing inner similarity. Firstly, we design a set of Gabor filters to compute the amplitude responses of original image and compute the texture map by a salience model. Secondly, we employ the simple clustering to extract superpixles by affinity of color, coordinates and texture map. Then, we design a normalized histograms descriptor for superpixels integrated color and texture information of inner pixels. To obtain the final segmentation result, all adjacent superpixels are merged by the homogeneity comparison of normalized color-texture features until the stop criteria is satisfied. The experiments are conducted on natural scene images and synthesis texture images demonstrate that the proposed segmentation algorithm can achieve ideal segmentation on complex texture regions.
Keywords
image segmentation; Gabor filters; color-texture histograms; region merging;
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1 Mousumi Gupta, Debasish Bhaskar et al. "Target detection of ISAR data by principal component transform on co-occurrence matrix," Pattern Recognition letter, vol. 33, no. 13, pp. 1682-1688, 2012.   DOI   ScienceOn
2 S E Grigorescu, N Petkov, P Kruizinga, "Comparison of Texture Features Based on Gabor Filters," IEEE Transaction on Image Process, vol. 11, no. 10, pp. 1160-1167, 2002.   DOI   ScienceOn
3 M K Bashar, T Matsumoto, N Ohnishi, "Wavelet Transform based Locally Orderless Images for Texture Segmentation," Pattern Recognition letter, vol. 24, no. 15, pp. 2633-2650, 2003.   DOI   ScienceOn
4 Zoltan Kato, Ting-Chuen Pong, "A Markov random field image segmentation model for color textured images," Image Vision Computing, vol .24, no. 10, pp. 1103-1114, 2006.   DOI   ScienceOn
5 Liang KH, Tjahjadi T, "Adaptive scale fixing for multiscale texture segmentation," IEEE Transaction on Image Process, vol. 15, no. 1, pp. 249-256, 2006.   DOI   ScienceOn
6 D. Comaniciu and P. Meer, "Mean shift: A robust approach toward feature space analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 5, pp. 603-619, 2002.   DOI   ScienceOn
7 Osvaldo Severino Jr., Adilson Gonzaga," A new approach for color image segmentation based on color mixture," Machine Vision and Application, vol. 24, pp. 607-618, 2013.   DOI
8 Xiuwen Liu, DeLiang Wang, "Image and Texture Segmentation Using Local Spectral Histograms," IEEE Transaction on Image Process, vol.15, no.10, pp. 3066-3077, 2006.   DOI   ScienceOn
9 T. Cour, F. Benezit, and J. Shi, " Spectral segmentation with multiscale graph decomposition," in Proc. of the IEEE International conference on Computer Vision and Pattern Recognition, vol. 2, pp. 1124-1131, 2005.
10 Luc Vincent and Pierre Soille, " Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, no. 6, pp. 583-598, 1991.   DOI   ScienceOn
11 Jeong Y S, Lim C G, Jeong B S, et al. "Topic Masks for Image Segmentation," KSII Transactions on Internet & Information Systems, vol. 7, no. 12, pp. 3274-3292, 2013. http://www.itiis.org/tiis/ download.jsp ?filename =TIIS%20Vol%207,%20No%2012-18.pdf   DOI   ScienceOn
12 S.-C. Zhu and A. Yuille, Region Competition, "Unifying Snakes, Region Growing, and Bayes/ MDL for Multiband Image Segmentation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no .9, pp. 884-900, 1996.   DOI   ScienceOn
13 Wenbing Tao, Hai Jin, Yimin Zhang, "Color Image Segmentation Based on Mean Shift and Graph Cuts," IEEE Transaction on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 37 no. 5, pp. 1382 -1389, 2007.
14 H. D Cheng, Y. Sun, "A hierarchical approach to color image segmentation using homogeneity," IEEE Transaction on Image Process 9(12), 2071-2082, 2000.   DOI   ScienceOn
15 KuanYu-hsin, Kuo Chuag-ming,Yang Nai-chung,"Color-based image salient region segmentation using novel region merging strategy," IEEE Transaction on Multimedia, vol. 10, no. 5, pp. 832- 845, 2008.   DOI   ScienceOn
16 A Y Yang, J Wright, Y Ma, " Unsupervised segmentation of natural images via lossy data compression," Comput Vis Image Und. 110(2),212-225, 2008.   DOI   ScienceOn
17 J. Ning, L. Zhang, David Zhang and C. Wu, "Interactive Image Segmentation by Maximal Similarity based Region Merging ," Pattern Recognition, vol. 43, no. 2, pp. 445-456, 2010.   DOI   ScienceOn
18 Bo Peng, Lei Zhang and Jian Yang, " Iterated Graph Cuts for Image Segmentation," in Proc. of the Asian Conference on Computer Vision, pp. 677-686, 2009.
19 Tamura H, Moil S, Yamawaki T, " Texture features corresponding to visual perception," IEEE Transaction on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 8, no. 6, 460-473,1978.   DOI   ScienceOn
20 Y.Deng, B.S.Manjunath, "Unsupervised segmentation of color-texture regions in images and video," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 8, pp. 800- 810, 2001.   DOI   ScienceOn
21 George Paschos, Maria Petrou, " Histogram ratio features for color texture classification," Pattern Recognition letter, vol. 24, pp. 309-314, 2003.   DOI   ScienceOn
22 M.-M. Cheng, G.-X. Zhang, N.J. Mitra, X. Huang, S.-M. Hu, " Global contrast based salient region detection," in Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 21-23. 2011.
23 H. Ling and K. Okada, " An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 5, pp. 840-853,(2007)   DOI   ScienceOn
24 J. S. Kim and K. S. Hong, " Color-texture segmentation using unsupervised graph cuts," Pattern Recognition, vol.42 , no. 5, pp. 735-750, 2009.   DOI   ScienceOn
25 Estrada, F.J., Jepson, A.D, " Quantitative Evaluation of a Novel Image Segmentation Algorithm," in Proc. of the IEEE International Conference on Computer Vision and Pattern Recognition, pp. 1132-1139, 2005.
26 MIT Vis Texture database. http://vismod.media.mit.edu/vismod/imagery/VisionTexture/ vistex. html
27 Zhenguo Li,Xiao-Ming Wu, Shih-Fu Chang, " Segmentation using superpixels: A Bipartite graph partitioning approach," in Proc. of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 789 -796, 2012.
28 R. Unnikrishnan, C. Pantofaru, and M. Hebert, "Toward objective evaluation of image segmentation algorithms," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 6, pp. 929-944, 2007.   DOI   ScienceOn
29 R.Unnikrishnan,C. Pantofaru, and M. Hebert,"Toward objective evaluation of image segmentation algorithms," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 6, pp. 929-944, 2007.   DOI   ScienceOn
30 D. Martin, C. Fowlkes, D. Tal, J. Malik, "A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics," in Proc. of IEEE International Conference on Computer Vision, pp. 416-423, 2001.
31 T. Leung, J. Malik, "Representing and recognizing the visual appearance of materials using threedimensional textons," International Journal of Computer Vision, vol. 43, no. 1, pp. 29-44. 2001.   DOI   ScienceOn
32 Achanta R, Hemami S, Estrada F, et al. "Frequency-tuned salient region detection," in Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1597-1604, 2009.
33 Ibrahim M T, Khan T M, Khan MA, "Automatic segmentation of pupil using local histogram and standard deviation," in Proc. of Visual Communications and Image Processing, pp. 77442S-77442S -8, 2010.
34 Wang M, Hua X S. "Active learning in multimedia annotation and retrieval: A survey." ACM Transactions on Intelligent Systems and Technology, vol. 2. no. 2, 10, 2011
35 Hong, Richang, et al. "Image Annotation By Multiple-Instance Learning With Discriminative Feature Mapping and Selection," IEEE Transactions on Cybernetics, vol. 44, no. 5, pp. 669-680 2014.   DOI   ScienceOn
36 Wang, Meng, et al. "Assistive tagging: A survey of multimedia tagging with human-computer joint exploration," ACM Computing Surveys, vol. 44. no. 4 , 25, 2012.
37 Nianhua Xie, Haibin Ling, Weiming Hu, and Xiaoqin Zhang, " Use Bin-Ratio Information for Category and Scene Classification." in Proc of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2313-2319, 2010.
38 Tuceryan M,Jain A K, Texture Analysis: Handbook Pattern Recognition and Computer Vision, 2nd Edition, Singapore World Scientific, pp. 207-248, 1999.
39 Zheng H, Ye Q, Jin Z. "A Novel Multiple Kernel Sparse Representation based Classification for Face Recognition," KSII Transactions on Internet & Information Systems, vol. 8, no. 4, pp. 1463-1480, 2014. http://www.itiis.org/tiis/download.jsp?filename=TIIS%20Vol%208,%20No% 204-17.pdf   DOI   ScienceOn
40 Yang K, Hua X S, Wang M, et al. "Tag tagging: Towards more descriptive keywords of image content," IEEE Transactions on Multimedia, vol. 13, no. 4 : 662-673, 2011.   DOI   ScienceOn
41 D.Martin, C.Fowlkes, and J. Malik, "Learning to detect natural image boundaries using local brightness, color, and texture cues," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol .26, no.5, pp. 530-549 , 2004.   DOI   ScienceOn
42 Christoph Palm, "Color Texture Classification by Integrative Co-occurrence Matrices," Pattern Recognition, vol. 37, no .5, pp. 965- 976, 2004.   DOI   ScienceOn
43 X. Ren and J. Malik, "Learning a classification model for segmentation," in Proc. of the Asian Conference on Computer Vision, pp. 10-17, 2003.
44 D. Hoiem, A. Efros, and M. Hebert, "Geometric context from a single image," in Proc. of the IEEE International conference on Computer Vision, pp. 654-661,2005.
45 G. Mori, X. Ren, A. Efros, and J. Malik, "Recovering human body configurations: Combining segmentation and recognition," in Proc. of the IEEE International conference on Computer Vision and Pattern Recognition, vol. 2, pp.326-333, 2004.
46 D. Hoiem, A. Efros, and M. Hebert, "Automatic photo pop-up," ACM Trans. Graph. 24(3), 577- 584, 2005.   DOI   ScienceOn
47 Ming-Yu Liu, Oncel Tuzel, Srikumar Ramalingam, Rama Chellappa, "Entropy rate superpixel segmentation," in Proc. of the IEEE International conference on Computer Vision and Pattern Recognition , pp. 2097-2104, 2011.
48 P. F. Felzenszwalb and D. P. Huttenlocher, "Efficient graph based image segmentation," International Journal of Computer Vision, vol. 59, no. 2, pp. 167-181, 2004.   DOI
49 D.Wang, "A multiscale gradient algorithm for image segmentation using watershelds," Pattern Recognition, vol. 30, no. 12, pp. 2043-2052,1997.   DOI   ScienceOn
50 Meyer, F, "An overview of morphological segmentation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 7, pp. 1089-1118 , 2001.
51 R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua and S. Süsstrunk, "SLIC Superpixels Compared to State-of-the-art Superpixel Methods," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 11, pp. 2274 - 2282, 2012.   DOI   ScienceOn
52 Fabio Drucker and John MacCormick, "Fast Superpixels for Video Analysis," In: Proc of the International conference on Motion and Video computing. pp. 55-62, 2009.
53 A. Levinshtein, A. Stere, K. N. Kutulakos, D. J. Fleet, S. J. Dickinson, and K. Siddiqi, "TurboPixels: Fast Superpixels Using Geometric Flows," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 12, pp. 2290-2297, 2009.   DOI   ScienceOn