Image Retrieval: Color and Texture Combining Based on Query-Image

  • Ilya Markov
  • Natalia Vassilieva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5099)

Abstract

It is a common way to process different image features independently in order to measure similarity between images. Color and texture are the common ones to use for searching in natural images. In [10] a technique to combine color and texture features based on a particular query-image in order to improve retrieval efficiency was proposed. Weighted linear combination of color and texture metrics was considered as a mixed-metrics. In this paper the mixed-metrics with different weights are compared to pure color and texture metrics and widely used CombMNZ data fusion algorithm. Experiments show that proposed metrics outperform CombMNZ method in some cases, and have close results in others.

Keywords

Content-Based Image Retrieval Mixed-Metrics Data Fusion 

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References

  1. 1.
    Aksoy, S., Haralick, R.M., Cheikh, F.A., Gabbouj, M.: A Weighted Distance Approach to Relevance Feedback. In: 15th International Conference on Pattern Recognition, vol. 4, pp. 812–815 (2000)Google Scholar
  2. 2.
    Borgne, H., Guerin-Dugue, A., Antoniadis, A.: Representation of images for classification with independent features. Pattern Recognition Letters 25, 141–154 (2004)CrossRefGoogle Scholar
  3. 3.
    Deer, P.J., Eklund, P.W.: On the Fusion of Image Features, http://citeseer.ist.psu.edu/162546.html
  4. 4.
    Fox, E.A., Shaw, J.A.: Combination of multiple searches. TREC 2, 243–249 (1994)Google Scholar
  5. 5.
    Guerin-Dugue, A., Ayache, S., Berrut, C.: Image retrieval: a first step for a human centered approach. In: Joint Conference of ICI, CSP and PRCM, vol. 1, pp. 21 – 25 (2003)Google Scholar
  6. 6.
    Howarth, P., Rueger, S.: Robust texture features for still image retrieval. In: IEE Proc. of Vision, Image and Signal Processing, vol. 152(6), pp. 868–874 (2005)Google Scholar
  7. 7.
    Lee, J.H.: Analyses of Multiple Evidence Combination. In: ACM-SIGIR, USA, pp. 267–276 (1997)Google Scholar
  8. 8.
    Lilis, D., Toolan, F., Mur, A., Peng, L., Colier, R., Dunnion, J.: Probability-Based Fusion of Information Retrieval Result Sets. J. Artif. Intell. Rev. 25(1-2), 179–191 (2006)CrossRefGoogle Scholar
  9. 9.
    Manjunath, B.S., Ma, W.Y.: Texture features for browsing and retrieval of image data. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(8), 837–842 (1996)CrossRefGoogle Scholar
  10. 10.
    Markov, I., Vassilieva, N., Yaremchuk, A.: Image retrieval. Optimal weights for color and texture features combining based on query object. In: Proc. of RCDL, Russia, pp. 195–200 (2007)Google Scholar
  11. 11.
    Montague, M., Aslam, J.A.: Relevance Score Normalization for Metasearch. In: ACM Conference on Information and Knowledge Management, pp. 427–433 (2001)Google Scholar
  12. 12.
    Rui, Y., Huang, T.S., Chang, S.-F.: Image Retrieval: Past, Present and Future. In: International Symposium on Multimedia Information Processing (1997)Google Scholar
  13. 13.
    Snitkowska, E., Kasprzak, W.: Independent Component Analysis of Textures in Angiography Images. Computational Imaging and Vision 32, 367–372 (2006)CrossRefGoogle Scholar
  14. 14.
    Stricker, M., Dimai, A.: Color Indexing with Weak Spatial Constraints. In: Storage and Retrieval for Image and Video Databases (SPIE), pp. 26–40 (1996)Google Scholar
  15. 15.
    Stricker, M., Dimai, A.: Spectral Covariance and Fuzzy Regions for Image Indexing. In: Machine Vision and Applications, vol. 10, pp. 66–73 (1997)Google Scholar
  16. 16.
    Swain, M., Ballard, D.: Color Indexing. International Journal of Computer Vision 7(1), 11–32 (1991)CrossRefGoogle Scholar
  17. 17.
    Vassilieva, N., Dolnik, A., Markov, I.: Image retrieval. Fusion of the result sets retrieved by using different image characteristics. Internet-mathematics Collection, 46–55 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ilya Markov
    • 1
  • Natalia Vassilieva
    • 2
  1. 1.Saint-Petersburg State UniversityRussia
  2. 2.HP LabsSaint-PetersburgRussia

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