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http://dx.doi.org/10.3745/JIPS.02.0060

Content-Based Image Retrieval Using Combined Color and Texture Features Extracted by Multi-resolution Multi-direction Filtering  

Bu, Hee-Hyung (School of Electronic Engineering, Kyungpook National University)
Kim, Nam-Chul (School of Electronic Engineering, Kyungpook National University)
Moon, Chae-Joo (Dept. of Electrical Engineering, Mokpo National University)
Kim, Jong-Hwa (Dept. of Compouter Engineering, Mokpo National University)
Publication Information
Journal of Information Processing Systems / v.13, no.3, 2017 , pp. 464-475 More about this Journal
Abstract
In this paper, we present a new texture image retrieval method which combines color and texture features extracted from images by a set of multi-resolution multi-direction (MRMD) filters. The MRMD filter set chosen is simple and can be separable to low and high frequency information, and provides efficient multi-resolution and multi-direction analysis. The color space used is HSV color space separable to hue, saturation, and value components, which are easily analyzed as showing characteristics similar to the human visual system. This experiment is conducted by comparing precision vs. recall of retrieval and feature vector dimensions. Images for experiments include Corel DB and VisTex DB; Corel_MR DB and VisTex_MR DB, which are transformed from the aforementioned two DBs to have multi-resolution images; and Corel_MD DB and VisTex_MD DB, transformed from the two DBs to have multi-direction images. According to the experimental results, the proposed method improves upon the existing methods in aspects of precision and recall of retrieval, and also reduces feature vector dimensions.
Keywords
Color and Texture Feature; Content-Based Image Retrieval; HSV Color Space; Multi-resolution Multi-direction Filtering;
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1 S. M. Singh and K. Hemachndran, "Image retrieval based on the combination of color histogram and color moment," International Journal of Computer Applications, vol. 58, no. 3, pp. 27-34, 2012.   DOI
2 M. J. Swain and D. H. Ballard, "Color indexing," International Journal of Computer Vision. vol. 7, no 1, pp. 11-32, 1991.   DOI
3 J. X. Zeng, Y. G. Zhao, and X. Fu, "A novel shape representation and retrieval algorithm: distance autocorrelogram," Journal of Software, vol. 5, no. 9, pp. 1022-1029, 2010.
4 J. Huang, S. R. Kumar, M. Mitra, W. J. Zhu, and R. Zabih, "Image indexing using color correlograms," in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, 1997, pp. 762-768.
5 ISO/IEC 15938-3/FDIS Information Technology - Multimedia Content Description Interface - Part 3: Visual, ISO/IEC/JTC 1/SC 29/WG 11, Doc. N4358, 2001.
6 R. Das, S. Thepade, and S. Ghosh, "Framework for content-based image identification with standardized multiview features," ETRI Journal, vol. 38, no. 1, pp. 174-184, 2016.   DOI
7 R. M. Haralick, K. Shanmugam, and I. Dinstein, "Texture features for image classification," IEEE Transactions on Systems, Man, and Cybernetics, vol. 3, no. 6, pp. 610-621, 1973.   DOI
8 C. Anibou, M. N. Saidi, and D. Aboutajdine, "Classification of textured images based on discrete wavelet transform and information fusion," Journal of Information Processing Systems, vol. 11, no. 3, pp. 421-437, 2015.   DOI
9 J. Han and K. K. Ma, "Rotation-invariant and scale-invariant Gabor features for texture image retrieval," Journal of Image and Vision Computing, vol. 25, no. 9, pp. 1474-1481, 2007.   DOI
10 T. W. Chiang, T. Tsai, and Y. P. Huang, "Image retrieval based on the wavelet features of interest," in Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, Taipei, Taiwan, 2006, pp. 3324-3329.
11 N. C. T. Hai, D. Y. Kim, and H. R. Park, "Texture comparison with an orientation matching scheme," Journal of Information Processing Systems, vol. 8, no. 3, pp. 389-398, 2012.   DOI
12 S. K. Chang, Principles of Pictorial Information Systems Design. Englewood Cliffs, NJ: Prentice-Hall, 1989, pp. 61-81.
13 Y. D. Chun, S. Y. Seo, and N. C. Kim, "Image retrieval using BDIP and BVLC moments," IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, no. 9, pp. 951-957, 2003.   DOI
14 H. Mahi, H. Isabaten, and C. Serief, "Zernike moments and SVM for shape classification in very high resolution satellite images," International Arab Journal of Information Technology, vol. 11, no. 1, pp. 43-51, 2014.
15 S. Agarwal, A. K. Verma, and P. Singh, "Content based image retrieval using discrete wavelet transform and edge histogram Descriptor," in Proceedings of International Conference on Information Systems and Computer Networks, Mathura, India, 2013, pp. 19-23.
16 M. R. Teague, "Image analysis via the general theory of moments," Journal of the Optical Society of America, vol. 70, no. 8, pp. 920-930, 1980.   DOI
17 M. K. Hu, "Visual pattern recognition by moment invariants," IRE Transactions on Information Theory, vol. 8, no. 2, pp. 179-187, 1962.
18 C. S. Lin and C. L. Hwang, "New forms of shape invariants from elliptic Fourier descriptors," Pattern Recognition, vol. 20, no. 5, pp. 535-545, 1987.   DOI
19 H. L. Beus and S. H. Tiu, "An improved corner detection algorithm based on chain coded plane curve," Pattern Recognition, vol. 20, no. 3, pp. 291-296, 1987.   DOI
20 Y. D. Chun, N. C. Kim, and I. H. Jang, "Content-based image retrieval using multiresolution color and texture features," IEEE Transactions on Multimedia, vol. 10, no. 6, pp. 1073-1084, 2008.   DOI
21 A. Anandh, K. Mala, and S. Suganya, "Content based image retrieval system based on semantic information using color, texture and shape features," in Proceedings of International Conference on Computing Technologies and Intelligent Data Engineering, Kovilpatti, India, 2016, pp. 1-8.
22 R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed. Upper Saddle River, NJ: Prentice Hall, 2002.
23 D. Comaniciu, P. Meer, K. Xu, and D. Tyler, "Retrieval performance improvement through low rank corrections," in Proceedings of IEEE Workshop on Content-Based Access of Image and Video Libraries, Fort Collins, CO, 1999, pp. 50-54.
24 N. K. Patil, R. M. Yadahalli, and J. Pujari, "Comparison between HSV and YCbCr color model color-texture based classification of the food grains," International Journal of Computer Applications, vol. 34, no. 4, pp. 51-57, 2011.
25 K. Khongkraphan, "An efficient color edge detection using the Mahalanobis distance," Journal of Information Processing Systems, vol. 10, no. 4, pp. 589-601, 2014.   DOI
26 S. Sural, G. Qian, and S. Pramanik, "Segmentation and histogram generation using the HSV color space for image retrieval," in Proceedings of IEEE International Conference on Image Processing, Rochester, NY, 2002, pp. 589-592.
27 C.Y. Chang, L. C. Chen, W. C. Lee, and C. C. Ma, "Measuring full-field deformation and vibration using digital image correlation," in Proceedings of the 14th IFToMM World Congress, Taipei, Taiwan, 2015, pp. 635-640.
28 W. Y. Ma and B. S. Manjunath, "A comparison of wavelet transform feature for texture image annotation," in Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, Washington, DC, 1995, pp. 256-259.