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Image Retrieval Based on Co-occurrence Matrix Using Block Classification Characteristics

  • Tae-Su Kim
  • Seung-Jin Kim
  • Kuhn-Il Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3767)

Abstract

A new method of content-based image retrieval is presented that uses the color co-occurrence matrix that is adaptive to the classification characteristics of the image blocks. In the proposed method, the color feature vectors are extracted according to the characteristics of the block classification after dividing the image into blocks with a fixed size. The divided blocks are then classified as either luminance or color blocks depending on the average saturation of the block in the HSI (hue, saturation, and intensity) domain. Thereafter, the color feature vectors are extracted by calculating the co-occurrence matrix of a block average intensity for the luminance blocks and the co-occurrence matrix of a block average hue and saturation for the color blocks. In addition, block directional pattern feature vectors are extracted by calculating histograms after directional gradient classification of the intensity. Experimental results show that the proposed method can outperform conventional methods as regards a precision and a feature vector dimension.

Keywords

Feature Vector Image Retrieval Query Image Color Histogram Vector Dimension 
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.

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References

  1. 1.
    Swain, M.J., Ballard, D.H.: Color indexing. Int. J. Comput. Vis. 7(1), 11–32 (1991)CrossRefGoogle Scholar
  2. 2.
    Huang, J., Kumar, S.R., Mitra, M., Zhu, W.-J., Zabih, R.: Image indexing using color correlegram. In: Proc. CVPR 1997, pp. 762–768 (1997)Google Scholar
  3. 3.
    Qiu, G.: Color image indexing using BTC. IEEE Trans. Image Processing 12(1), 93–101 (2003)CrossRefGoogle Scholar
  4. 4.
    Nezamabadi-pour, H., Kabir, E.: Image retrieval using histograms of uni-color and bi-color blocks and directional changes in intensity gradient. Pattern Recogn. Lett. 25(14), 1547–1557 (2004)CrossRefGoogle Scholar
  5. 5.
    Rui, Y., Huang, T.S., Chang, S.-F.: Image retrieval: Current techniques, promising directions, and open issues. J. Vis. Commun. Image Represent. 10(1), 39–62 (1999)CrossRefGoogle Scholar
  6. 6.
    Wang, J.Z., Li, J., Wiederhold, G.: Simplicity: semantics-integrated matching for picture libraries. IEEE Trans. Pattern Anal. Machine Intell. 23(9), 947–963 (2001)CrossRefGoogle Scholar
  7. 7.
    Chen, D., Bovik, A.C.: Visual pattern image coding. IEEE Trans. Commun. 38(12), 2137–2146 (1990)CrossRefGoogle Scholar
  8. 8.
    Mojsilovic, A., Hu, H., Soljanin, E.: Extraction of perceptually important colors and similarity measurement for image matching, retrieval, and analysis. IEEE Trans. Image Processing 11(11), 1238–1248 (2002)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Sikora, T.: The MPEG-7 visual standard for content description-an overview. IEEE Trans. Circuits Syst. Video Technol. 11(6), 696–702 (2001)CrossRefMathSciNetGoogle Scholar
  10. 10.
    Mirmehdi, M., Perissamy, R.: Perceptual image indexing and retrieval. J. Vis. Commun. Image Represent. 13(4), 460–475 (2002)CrossRefGoogle Scholar
  11. 11.
    Aslandogan, Y.A., Yu, C.T.: Techniques and systems for image and video retrieval. IEEE Trans. Knowl. Data Eng. 11(1), 56–63 (1999)CrossRefGoogle Scholar
  12. 12.
    Sural, S., Quin, G., Pramanik, S.: Segmentation and histogram generation using HSV color space for image retrieval. In: Proc. of ICIP, vol. 2(2), pp. 589–592 (2002)Google Scholar
  13. 13.
    Park, D.K., Jeon, Y.S., Won, C.S., Park, S.J., Yoo, S.J.: A composite histogram for image retrieval. In: Proc. of ICME, vol. 1, pp. 355–358 (2000)Google Scholar
  14. 14.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing, pp. 295–302. Prentice Hall, Englewood Cliffs (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Tae-Su Kim
    • 1
  • Seung-Jin Kim
    • 1
  • Kuhn-Il Lee
    • 1
  1. 1.School of Electrical Engineering and Computer ScienceKyungpook National UniversityDaeguKorea

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