CONTENT-BASED TEXTURE IMAGE RETRIEVAL USING THE LEMPEL-ZIV-WELCH ALGORITHM

Leonardo Vidal Batista, Moab Mariz Meira, Nicomedes L. Cavalcanti Júnior

2006

Abstract

This paper presents a method for content-based texture image retrieval using the Lempel-Ziv-Welch (LZW) compression algorithm. Each texture image in the database is processed by a global histogram equalization filter, and then an LZW dictionary is constructed for the filtered texture and stored in the database. The LZW dictionaries thus constructed comprise a statistical model to the texture. In the query stage, each texture sample to be searched is processed by the histogram equalization filter and successively encoded by the LZW algorithm in static mode, using the stored dictionaries. The system retrieves a ranked list of images, sorted according to the coding rate achieved with each stored dictionary. Empirical results with textures from the Brodatz album show that the method achieves retrieval accuracy close to 100%.

References

  1. Addis, M., Lewis, P., and Martinez, K. (2002). Artiste image retrieval system puts european galleries in the picture. Cultivate Interactive, (7).
  2. Augusteijn, M. F., Clemens, L. E., and Shaw, K. A. (1995). Performance evaluation of texture measures for ground cover identification in satellite images by means of a neural network classifier. IEEE Transactions on Geoscience and Remote Sensing, 33(3):616- 626.
  3. Bach, J. R., Fuller, C., Gupta, A., Hampapur, A., B. Horowitz, R. H., Jain, R., and Shu, C. F. (1996). The virage image search engine: An open framework for image management. In Proc. SPIE Storage and Retrieval for Image and Video Databases IV, San Jose, CA, USA.
  4. (1999). New texture features based on the complexity curve. Pattern Recognition, 32(4):605-618.
  5. Bell, T. C., Cleary, J. G., and Witten, J. H. (1990). Text Compression. Englewood Cliffs: Prentice-Hall.
  6. Bovik, A. e. (2000). Handbook of Image and Video Processing. San Diego: Academic Press.
  7. Brodatz, P. (1966). Textures: A Photographic Album for Artists and Designers. New York: Dover.
  8. Dell'Acqua, F. and Gamba, P. (2003). Texture-based characterization of urban environments on satellite sar images. IEEE Transactions on Geoscience and Remote Sensing, 41(1):153-159.
  9. Dowe, J. (1993). Content-based retrieval in multimedia imaging. In Proc. SPIE Storage and Retrieval for Image and Video Databases.
  10. Faloutsos, C., Flickner, M., Niblack, W., Petkovic, D., Equitz, W., and Barber, R. (1993). Efficient and effective querying by image content. Tech. Rep., IBM Res. Rep.
  11. Finamore, W. and Leister, M. A. (1996). Lossy lempel-ziv algorithm for large alphabet sources and applications to image compression. volume 1, pages 235-238.
  12. Flickner, M., Sawhney, H., Niblack, W., Ashley, J., Huang, Q., Dom, B., Gorkani, M., Hafine, J., Lee, D., Petkovic, D., Steele, D., and Yanker, P. (1995). Query by image and video content: The qbic system. IEEE Computer.
  13. Frank, E., Chui, C., and Witten, I. H. (2000). Text categorization using compression models. In Storer, J. A. and Cohn, M., editors, Proceedings of DCC00, IEEE Data Compression Conference, pages 200- 209, Snowbird, US. IEEE Computer Society Press, Los Alamitos, US.
  14. He, X., Hu, Y., Zhang, H., Li, M., Cheng, Q., and Yan, S. (2004). Bayesian shape localization for face recognition using global and local textures. IEEE Transactions on Circuits and Systems for Video Technology, 14(1):102-113.
  15. Huang, T., Mehrotra, S., and Ramchandran, K. (1996). Multimedia analysis and retrieval system (mars) project. In Proc. 33rd Annu. Clinic Library Appl. of Data Processing Digital Image Access and Retrieval.
  16. ISO/IEC, JTC1/SC29/WG11, and N1920 (1997a). Mpeg-7: Context and objectives (v.5).
  17. ISO/IEC, JTC1/SC29/WG11, and N1921 (1997b). Third draft of mpeg-7 requirements.
  18. ISO/IEC, JTC1/SC29/WG11, and N1922 (1997c). Mpeg-7 applications document.
  19. Jain, A. K., Ross, A., and Prabhakar, S. (2004). An introduction to biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology, 14(1):4-20.
  20. Jain, R. (1993). Nsf workshop on visual information management systems. SIGMOD Rec., 22(3):57-75.
  21. Jain, R., Pentland, A., and Petkovic, D. (1995). NSF-ARPA workshop visual inform. management syst.
  22. Kumar, A. and Pang, G. K. H. (2002). Defect detection in textured materials using optimized filters systems. IEEE Transactions on Man and Cybernetics, Part B: Cybernetics, 32(5):553-570.
  23. Ma, W.-Y. and Manjunath, B. S. (1999). Netra: A toolbox for navigating large image databases. Multimedia Systems, 7(3):184-198.
  24. Mandal, M. K., Panchanathan, S., and Aboulnasr, T. (1997). Image indexing using translation and scale-invariant moments and wavelets. In Storage and Retrieval for Image and Video Databases (SPIE), pages 380-389.
  25. Ojala, T., Pietikainen, M., and Maenpaa, T. (2002). Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7):971-987.
  26. Pentland, A., Picard, R. W., and Sclaroff, S. (1996). Photobook: content-based manipulation of image databases. Int. J. Comput. Vision, 18(3):233-254.
  27. Porat, M. and Zeevi, Y. Y. (1989). Localized texture processing in vision: Analysis and synthesis in the gaborian space. IEEE Transactions on Biomedical Engineering, 36(1):115-129.
  28. Randen, T. and Husy, J. H. (1999). Filtering for texture classification: a comparative study. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(4):291-310.
  29. Savari, S. A. (1997). Redundancy of the lempel-ziv-welch code. In Proc. DCC, Salt Lake City, pages 191-200.
  30. Shannon, C. E. (1948). A mathematical theory of communication. Bell Syst. Tech. J., 27:379-423.
  31. Smith, J. R. and Chang, S.-F. (1997). Visually searching the web for content. IEEE MultiMedia, 4(3):12-20.
  32. Southard, T. E. and Southard, K. A. (1996). Detection of simulated osteoporosis in maxillae using radiographic texture analysis. IEEE Transactions on Biomedical Engineering, 43(2):123-132.
  33. Teahan, W. J. and Harper, D. J. (2001). Using compressionbased language models for text categorization. In Workshop on Language Modeling and Information Retrieval, pages 83-88.
  34. Welch, T. A. (1984). A technique for high performance data compression. IEEE Computer, 17(6):8-19.
  35. Xu, K., Georgescu, B., Meer, P., and Comaniciu, D. (2000). Performance analysis in content-based retrieval with textures. In Proc. Int. Conf. Patt. Recog., volume 4, pages 275-278.
  36. Zibreira, C. (2000). Descric¸ a˜o e Procura de Vídeo Baseadas na Forma. Master thesis, Instituto Superior Técnico de Lisboa, Portugal.
  37. Ziv, J. (1988). On classification with empirically observed statistics and universal data compression. IEEE Transactions on Information Theory, 34(2):278-286.
  38. Ziv, J. and Lempel, A. (1978). Compression of individual sequences via variable-rate coding. IEEE Transactions on Information Theory, 24(5):530-536.
  39. Ziv, J. and Merhav, N. (1993). A measure of relative entropy between individual sequences with application to universal classification. IEEE Transactions on Information Theory, 39(4):1270-1279.
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Paper Citation


in Harvard Style

Vidal Batista L., Mariz Meira M. and L. Cavalcanti Júnior N. (2006). CONTENT-BASED TEXTURE IMAGE RETRIEVAL USING THE LEMPEL-ZIV-WELCH ALGORITHM . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 972-8865-40-6, pages 62-68. DOI: 10.5220/0001376600620068


in Bibtex Style

@conference{visapp06,
author={Leonardo Vidal Batista and Moab Mariz Meira and Nicomedes L. Cavalcanti Júnior},
title={CONTENT-BASED TEXTURE IMAGE RETRIEVAL USING THE LEMPEL-ZIV-WELCH ALGORITHM},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2006},
pages={62-68},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001376600620068},
isbn={972-8865-40-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - CONTENT-BASED TEXTURE IMAGE RETRIEVAL USING THE LEMPEL-ZIV-WELCH ALGORITHM
SN - 972-8865-40-6
AU - Vidal Batista L.
AU - Mariz Meira M.
AU - L. Cavalcanti Júnior N.
PY - 2006
SP - 62
EP - 68
DO - 10.5220/0001376600620068