Advertisement

Image Retrieval by Content Using Segmentation Approach

  • Bhogeswar Borah
  • Dhruba K. Bhattacharyya
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3776)

Abstract

This paper presents an efficient image retrieval technique based on content using segmentation approach and by considering global distribution of color. To cope with significant appearance changes, the method uses a global size and shape histogram to represent the image regions obtained after segmenting the image based on color similarity. The indexing technique can be found to be significant in comparison to its other counterparts, such as moment based method [12], due to its transformation invariance and effective retrieval performance over several application domains.

Keywords

Image Retrieval Query Image Retrieval Performance Segmentation Approach Segment Size 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Swain, M.J., Ballard, D.H.: Color Indexing. International Journal of Computer Vision 7(1), 11–32 (1991)CrossRefGoogle Scholar
  2. 2.
    Stricker, M., Orengo, M.: Similarity of Color Images. In: Proc. of SPIE Storage and Retrieval for Image and Video Databases, February 1995, vol. 2420, pp. 381–392 (1995)Google Scholar
  3. 3.
    Tao, Y., Grosky, W.I.: Spatial Color Indexing: A Novel Approach for Content-Based Image Retrieval. In: IEEE Intl. Conf. on Multimedia and Systems, June 1999, vol. 1, pp. 530–535 (1999)Google Scholar
  4. 4.
    Hsu, W., Chua, T.S., Pung, H.K.: An Integrated Color-Spatial Approach to Content-based Image Retrieval. In: Proc. of ACM Multimedia, San Francisco, California, November 1995, pp. 305–313 (1995)Google Scholar
  5. 5.
    Lee, H.Y., Lee, H.K., Ha, Y.H.: Spatial Color Descriptor for Image Retrieval and Video Segmentation. IEEE Transaction on Multimedia 5(3) (September 2003)Google Scholar
  6. 6.
    Pass, G., Zabih, R.: Histogram Refinement for Content-Based Image Retrieval. In: IEEE Workshop on Applications of Computer Vision, pp. 96–102 (1996)Google Scholar
  7. 7.
    Park, I.K., Yun, I.D., Lee, S.W.: Color image retrieval using hybrid graph representation. Image and Vision Computing 17(7), 465–474 (1999)CrossRefGoogle Scholar
  8. 8.
    Sethi, I.K., Coman, I., et al.: Color-WISE: A system for Image Similarity Retrieval Using Color. In: Proc. of SPIE Storage and Retrieval for Image and Video Databases, February 1998, vol. 3312, pp. 140–149 (1998)Google Scholar
  9. 9.
    Belongie, S., Carson, C., Greenspan, H., Malik, J.: Color and texture-Based Image Segmentation Using EM and Its Application to Content-Based Image Retrieval. In: Proc. of the Intl. Conf. on Computer Vision, ICCV 1998 (1998)Google Scholar
  10. 10.
    Mehtre, B.M., Kankanhalli, M.S., Lee, W.F.: Content-Based Image Retrieval Using A Composite Color-Shape Approach. Information Processing and Management 34(1), 109–120 (1998)CrossRefGoogle Scholar
  11. 11.
    Huang, J., Kumar, S.R., Mitra, M., Zhu, W.J., Zabih, R.: Image indexing Using Color Correlograms. In: Proc. of the 16th IEEE Conf. on Computer Vision and Pattern Recognition, June 1997, pp. 762–768 (1997)Google Scholar
  12. 12.
    Paschos, G., Radev, I., Prabakar, N.: Image Content-Based Retrieval Using Chromaticity Moments. IEEE Ttransaction on Knowledge and Data Engineering 15(5), 1069–1072 (2003)CrossRefGoogle Scholar
  13. 13.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn., Pearson Education (2003)Google Scholar
  14. 14.

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Bhogeswar Borah
    • 1
  • Dhruba K. Bhattacharyya
    • 1
  1. 1.Tezpur UniversityTezpurIndia

Personalised recommendations