Advertisement

A Novel Image Retrieval Approach Combining Multiple Features of Color-Connected Regions

  • Yubin Yang
  • Shifu Chen
  • Yao Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4031)

Abstract

This paper proposes a novel image retrieval method MCM (Multi-component Co-occurrence Matrices), which combines the color-connected regions in an image with their corresponding visual features in a region-growing like manner. Experimental results have shown that the MCM method has good retrieval performance and efficiency, due to the capability of integrating color composition, color spatial layout and texture characteristics into its coarse-granule region representation.

Keywords

Image Retrieval Query Image Dominant Color CBIR System Mosaic Block 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Malki, J., Boujemaa, N., Nastar, C., Winter, A.: Region queries without segmentation for image retrieval by content. In: Proceedings of Visual Information and Information Systems, Amsterdam, The Netherlands, June 2-4, pp. 115–122 (1999)Google Scholar
  2. 2.
    Fauqueur, J., Boujemaa, N.: Image retrieval by regions: coarse segmentation and fine color description. In: Chang, S.-K., Chen, Z., Lee, S.-Y. (eds.) VISUAL 2002. LNCS, vol. 2314, pp. 24–35. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  3. 3.
    Haralick, R.M.: Statistical and structural approaches to texture. Proceedings of the IEEE 67, 786–804 (1979)CrossRefGoogle Scholar
  4. 4.
    Whelan, P.F., Molloy, D.: Machine vision algorithms in Java: techniques and implementation. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  5. 5.
    Vassili, K., Stephan, V.: Color co-occurrence descriptors for querying-by-example. In: Proceedings of International Conference on Multimedia Modeling, Lausanne, Switzerland, October 12-15, pp. 32–37 (1998)Google Scholar
  6. 6.
    Takahashi, N., Iwasaki, M., Kunieda, T., et al.: Image retrieval using spatial intensity features. Signal Processing: Image Communication 16, 45–57 (2000)Google Scholar
  7. 7.
    Yang, Y.B.: Research and applications on the key techniques of content-based image retrieval. Ph.D. Thesis, Nanjing University, Nanjing, P.R. China (in Chinese) (2003)Google Scholar
  8. 8.
    Gaurav, S.: Digital color Imaging. IEEE Transactions On Image Processing 6(7), 901–932 (1997)CrossRefGoogle Scholar
  9. 9.
    Conners, R.W., Harlow, C.A.: A theoretical comparison of texture algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 2, 204–222 (1980)CrossRefMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yubin Yang
    • 1
  • Shifu Chen
    • 1
  • Yao Zhang
    • 2
  1. 1.State Key Laboratory for Novel Software TechnologyNanjing UniversityNanjingP.R. China
  2. 2.Department of Information ManagementNanjing UniversityNanjingP.R. China

Personalised recommendations