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An Efficient Perceptual Color Indexing Method for Content-Based Image Retrieval Using Uniform Color Space

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Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 285))

Abstract

Dominant Color Descriptor (DCD) is one of the famous descriptors in Content-based image retrieval (CBIR). Sequential search is one of the common drawbacks of most color descriptors especially in large databases. In this paper, dominant colors of an image are indexed to avoid sequential search in the database where uniform RGB color space is used to index images in LUV perceptual color space. Proposed indexing method will speed up the retrieval process where the dominant colors in query image are used to reduce the search space. Additionally, the accuracy of color descriptors is improved due to this space reduction. Experimental results show effectiveness of the proposed color indexing method in reducing search space to less than 25 % without degradation the accuracy.

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References

  1. Penatti, O. A. B., Valle, E., and Torres, R. d. S., “Comparative Study of Global Color and Texture Descriptors for Web Image Retrieval,” Journal of Visual Communication and Image Representation (Elsevier), 2012.

    Google Scholar 

  2. Talib, A., Mahmuddin, M., Husni, H., and George, L. E., “A weighted dominant color descriptor for content-based image retrieval,” Journal of Visual Communication and Image Representation, vol. 24, pp. 345-360, 2013.

    Google Scholar 

  3. Talib, A., Mahmuddin, M., Husni, H., and George, L. E., “Efficient, Compact, and Dominant Color Correlogram Descriptors for Content-based Image Retrieval,” presented at the MMEDIA 2013: Fifth International Conference on Advances in Multimedia, Venice, Italy, 22-26 April 2013, 2013.

    Google Scholar 

  4. Yamada, A., Pickering, M., Jeannin, S., and Jens, L. C., “MPEG-7 Visual Part of Experimentation Model Version 9.0-Part 3 Dominant Color,” ISO/IEC JTC1/SC29/WG11/N3914, Pisa, 2001.

    Google Scholar 

  5. Yang, N.-C., Chang, W.-H., Kuo, C.-M., and Li, T.-H., “A fast MPEG-7 dominant color extraction with new similarity measure for image retrieval,” Journal of Visual Communication and Image Representation, vol. 19 (2008), pp. 92–105, 2008.

    Google Scholar 

  6. Mojsilovic, A., Hu, J., and Soljanin, E., “Extraction of perceptually important colors and similarity measurement for image matching, retrieval, and analysis,” Transaction of Image Processing, vol. 11 (11), pp. 1238–1248, 2002.

    Google Scholar 

  7. Kiranyaz, S., Birinci, M., and Gabbouj, M., Perceptual Color Descriptors. Foveon, Inc./Sigma Corp., San Jose, California, USA: Boca Raton, FL, CRC Press, 2012.

    Google Scholar 

  8. Wong, K.-M., Po, L.-M., and Cheung, K.-W., “Dominant Color Structure Descriptor For Image Retrieval,” IEEE International Conference on Image Processing, 2007. ICIP 2007, vol. 6, pp. 365-368, 2007.

    Google Scholar 

  9. Jouili, S. and Tabbone, S., “Hypergraph-based image retrieval for graph-based representation,” Pattern Recognition, vol. 45, pp. 4054-4068, 2012.

    Google Scholar 

  10. Park, D.-S., Park, J.-S., Kim, T. Y., and Han, J. H., “Image indexing using weighted color histogram,” in Image Analysis and Processing, 1999. Proceedings. International Conference on, 1999, pp. 909-914.

    Google Scholar 

  11. Babu, G. P., Mehtre, B. M., and Kankanhalli, M. S., “Color indexing for efficient image retrieval,” Multimedia Tools and Applications, vol. 1 (November), pp. 327–348, 1995.

    Google Scholar 

  12. Sudhamani, M. and Venugopal, C., “Grouping and indexing color features for efficient image retrieval,” International. Journal of Applied Mathematics and Computer Sciences. v4 i3, pp. 150-155, 2007.

    Google Scholar 

  13. Sclaroff, S., Taycher, L., and Cascia, M. L., “Image-Rover: a content-based image browser for the world wide web,” Proceedings of IEEE Workshop on Content-based Access Image and Video Libraries, Puerto Rico, pp. 2-9, 1997.

    Google Scholar 

  14. Yildizer, E., Balci, A. M., Jarada, T. N., and Alhajj, R., “Integrating wavelets with clustering and indexing for effective content-based image retrieval,” Knowledge-Based Systems, vol. 31, pp. 55-66, 2012.

    Google Scholar 

  15. Gervautz, M. and Purgathofer, W., “A simple method for color quantization: Octree quantization,” in New trends in computer graphics, ed: Springer, 1988, pp. 219-231.

    Google Scholar 

  16. Deng, Y., Manjunath, B. S., Kenney, C., Moore, M. S., and Shin, H., “ An efficient color representation for image retrieval,” IEEE Trans. Image Process, vol. 10 (1), pp. 140–147, 2001.

    Google Scholar 

  17. Ma, W.-Y. and Manjunath, B. S., “Netra: A toolbox for navigating large image databases,” Multimedia systems, vol. 7, pp. 184-198, 1999.

    Google Scholar 

  18. Pauleve, L., Jegou, H., and Amsaleg, L., “Locality sensitive hashing: A comparison of hash function types and querying mechanisms,” Pattern Recognition Letter, vol. 31, pp. 1348-1358, 2010.

    Google Scholar 

  19. Renato, O. S., Mario, A. N., and Alexandre, X. F., “A Compact and Efficient Image Retrieval Approach Based on Border/Interior Pixel Classification,” Proceedings Information and Knowledge Management, pp. 102-109, 2002.

    Google Scholar 

  20. Kunttu, I., Lepistö, L., Rauhamaa, J., and Visa, A., “Image correlogram in image database indexing and retrieval,” Proceedings of 4th European Workshop on Image Analysis for Multimedia Interactive Services, London, UK, pp. 88-91, 2003.

    Google Scholar 

  21. Lightstone, S. S., Teorey, T. J., and Nadeau, T., Physical Database Design: the database professional’s guide to exploiting indexes, views, storage, and more., 2010.

    Google Scholar 

  22. Jiebo, L. and Crandall, D., “Color object detection using spatial-color joint probability functions,” IEEE Transactions on Image Processing, vol. 15, pp. 1443-1453, 2006.

    Google Scholar 

  23. Khan, F. S., Rao, M. A., Weijer, J. v. d., Bagdanov, A. D., Vanrell, M., and Lopez, A., “Color Attributes for Object Detection,” Twenty-Fifth IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2012), 2012.

    Google Scholar 

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Correspondence to Ahmed Talib .

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Talib, A., Mahmuddin, M., Husni, H., George, L.E. (2014). An Efficient Perceptual Color Indexing Method for Content-Based Image Retrieval Using Uniform Color Space. In: Herawan, T., Deris, M., Abawajy, J. (eds) Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013). Lecture Notes in Electrical Engineering, vol 285. Springer, Singapore. https://doi.org/10.1007/978-981-4585-18-7_45

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  • DOI: https://doi.org/10.1007/978-981-4585-18-7_45

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