Skip to main content

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 174))

  • 1941 Accesses

Abstract

There is a huge amount of methods for extracting image descriptors and defining the similarity measures. In this paper, we try to improve texture image retrieval performance with post processing based on the greedy technique called Prims algorithm. In the proposed method feature database is represented using distance matrix, which is the distance between every image of the database. Due to symmetric property of a matrix, we can improve the efficiency and effectiveness of the proposed retrieval system. However for large database the size of the matrix is large. The proposed system is tested with three different image descriptors, namely combined rotated complex wavelet filters (RCWF) and dual tree complex wavelets (DT-CWT), Contourlet Transform (CT), and Discrete Wavelet Transforms (DWT).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ritendra, D., Dhiraj, J., Jia, L., Wang, Z.J.: Image Retrieval: Ideas, Influ-ences, and Trends of the New Age. ACM Computing Surveys 40(2), article 5, 5:1–5:60 (2008)

    Google Scholar 

  2. Duncan, D.Y., Minh, N.D.: Directional Multiscale Modeling of Image using the Contourlet Transform. IEEE Transactions on Image Processing 15(6), 1610–1620 (2006)

    Article  MathSciNet  Google Scholar 

  3. He, J., Li, M., Zhang, H.J., Tong, H., Zhang, C.: Generalized Manifold-Ranking Based Image Retrieval. IEEE Transactions on Image Processing 15(10), 3170–3177 (2006)

    Article  Google Scholar 

  4. He, J., Li, M., Zhang, H.J., Tong, H., Zhang, C.: Manifold-Ranking Based Image Retrieval. In: ACM Multimedia (2004)

    Google Scholar 

  5. Kokare, M., Chatterji, B.N., Biswas, P.K.: A Survey on Current Content-based Image Retrieval Methods. IETE J. Res. 48(3&4), 261–271 (2002)

    Google Scholar 

  6. Kokare, M., Chatterji, B.N., Biswas, P.K.: Texture Image Retrieval using New Rotated Complex Wavelet Filters. IEEE Trans. on Systems, Man, and Cybernetics-Part B: Cybernetics 35(6), 1168–1178 (2005)

    Article  Google Scholar 

  7. Kingsbury, N.G.: Image processing with complex wavelet. Phil. Trans. Roy. Soc. London A 357, 2543–2560 (1999)

    Article  MATH  Google Scholar 

  8. Liua, Y., Zhang, D., Lua, G., Mab, W.Y.: A Survey of Content-Based Image Retrieval with high-level semantics. In: Proceedings of the Pattern Recognition, pp. 262–282 (2007)

    Google Scholar 

  9. Rui, Y., Hung, T.S., Chang, S.F.: Image retrieval: Current Techniques, Promising Directions and Open Issues. J. Visual Comm. and Image Representation 10, 39–62 (1999)

    Article  Google Scholar 

  10. Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content–Based Image Retrieval at the End of the Early Years. IEEE Trans. Pattern Anal. Machine Intell. 22(12), 1349–1380 (2000)

    Article  Google Scholar 

  11. Yang, X., Bai, X., Latecki, L.J., Tu, Z.: Improving Shape Retrieval by Learning Graph Transduction. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 788–801. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  12. Zhou, D., Bousquer, O., Lal, T., Weston, J., Schölkopf, B.: Learning with Local and Global Consistency. In: Proceedings of the Advances in Neural Information Processing Systems, pp. 321–328 (2004)

    Google Scholar 

  13. Zhou, D., Weston, J., Agretton: Ranking on Data Manifold. In: Proceedings of the Advances in Neural Information Processing Systems, pp. 169–176 (2004)

    Google Scholar 

  14. Zhou, D., Schölkopf, B.: Learning from Labeled and Unlabeled Data Using Random Walks. In: Rasmussen, C.E., Bülthoff, H.H., Schölkopf, B., Giese, M.A. (eds.) DAGM 2004. LNCS, vol. 3175, pp. 237–244. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pushpa B. Patil .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer India

About this paper

Cite this paper

Patil, P.B., Kokare, M.B. (2013). Texture Image Retrieval Using Greedy Method. In: Kumar M., A., R., S., Kumar, T. (eds) Proceedings of International Conference on Advances in Computing. Advances in Intelligent Systems and Computing, vol 174. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0740-5_106

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-0740-5_106

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-0739-9

  • Online ISBN: 978-81-322-0740-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics