Skip to main content

Region Based Image Retrieval Using Integrated Color, Texture and Shape Features

  • Conference paper
  • First Online:
Information Systems Design and Intelligent Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 340))

Abstract

In this paper a region based image retrieval scheme has been proposed based on integration of color, texture and shape features using local binary patterns (LBP). The color and texture features are extracted using LBP histograms of quantized color image and gray level images respectively. For improving the discrimination power of LBP, threshold computed using both centre pixel and its neighbors is used. Finally, shape features are computed using the binary edge map obtained using Sobel edge detector from each block. All three features are combined to make a single completed binary region descriptor (CBRD) represented in the LBP way. To support region based retrieval a more effective region code based scheme is employed. The spatial relative locations of objects are also considered to increase the retrieval accuracy.

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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

References

  1. Faloutsos, C., Barber, R., Flickner, M., Hafner, J., Niblack, W., Petkovic, D., Equitz, W.: Efficient and effective querying by image content. J. Intell. Inf. Syst. 3(3–4), 231–262 (1994)

    Article  Google Scholar 

  2. Pentland, A., Picard, R.W., Scaroff, S.: Photobook: content-based manipulation for image databases. Int. J. Comput. Vis. 18(3), 233–254 (1996)

    Article  Google Scholar 

  3. Gupta, A., Jain, R.: Visual information retrieval. Commun. ACM 40(5), 70–79 (1997)

    Google Scholar 

  4. Smith, J.R., Chang, S.F.: Visualseek: a fully automatic content-based query system. In: Proceedings of ACM International Conference on Multimedia, pp. 87–98 (1996)

    Google Scholar 

  5. Ma, W.Y., Manjunath, B.: Netra: a toolbox for navigating large image databases. In: Proceedings of International Conference on Image Processing, pp. 568–571 (1997)

    Google Scholar 

  6. Wong, K.-M., Cheung, K.-W., Po, L.-M.: MIRROR: an interactive content based image retrieval system. In: Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS 2005), vol. 2, pp. 1541–1544 (2005)

    Google Scholar 

  7. Broek, E.L., Kisters, P.M.F., Vuurpijl, L.G.: The utilization of human color categorization for content-based image retrieval. Proc. SPIE 5292, 351–362 (2004)

    Article  Google Scholar 

  8. Huang, C., Liu, Q., Yu, S.: Regions of interest extraction from color image based on visual saliency. J. Supercomput. 58(1), 20–33 (2011)

    Article  Google Scholar 

  9. Zhang, J., Yoo, C.W., Ha, S.W.: ROI based natural image retrieval using color and texture feature. Fuzzy Syst. Knowl. Discov. (2007)

    Google Scholar 

  10. Shrivastava, N., Tyagi, V.: Content based image retrieval based on relative locations of multiple regions of interest using selective regions matching. Inf. Sci. 259, 212–224 (2013)

    Article  Google Scholar 

  11. Tian, Q., Wu, Y., Huang, T.S.: Combine user defined region-of-interest and spatial layout for image retrieval. In: Proceedings of IEEE International Conference on Image Processing (ICIP’2000), vol. 3, pp. 746–749 (2000)

    Google Scholar 

  12. Prasad, B.G., Biswas, K.K., Gupta, S.K.: Region-based image retrieval using integrated color, shape and location index. Comput. Vis. Image Underst. 94, 193–233 (2004)

    Article  Google Scholar 

  13. Moghaddam, B., Biermann, H., Margaritis, D.: Regions-of-interest and spatial layout for content-based image retrieval. Multimedia Tools Appl. 14(2), 201–210 (2001)

    Article  Google Scholar 

  14. Lee, J., Nang, J.: Content-based image retrieval method using the relative location of multiple ROIs. Adv. Electr. Comput. Eng. 11(3), 85–90 (2011)

    Article  Google Scholar 

  15. Shrivastava, N., Tyagi, V.: A review of ROI image retrieval techniques. Adv. Intell. Syst. Comput. 328, 509–520 (2015). doi:10.1007/978-3-319-12012-6_56

    Article  Google Scholar 

  16. Liu, G.H., Yang, J.Y.: Image retrieval based on the texton co-occurrence matrix. Pattern Recogn. 41(12), 3521–3527 (2008)

    Article  MATH  Google Scholar 

  17. Shrivastava, N., Tyagi, V.: An effective scheme for image texture classification based on binary local structure pattern. Visual Comput. 30(11), 1223–1232 (2014). doi:http://dx.doi.org/10.1007/s00371-013-0887-0

  18. http://wang.ist.psu.edu/docs/related/

  19. Liu, G.H., Li, Z.Y., Zhang, L., Xu, Y.: Image retrieval based on micro-structure descriptor. Pattern Recogn. 44(9), 2123–2133 (2011)

    Article  Google Scholar 

  20. Wang, X., Wang, Z.: A novel method for image retrieval based on structure elements descriptor. J. Vis. Commun. Image Represent. 24, 63–74 (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vipin Tyagi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer India

About this paper

Cite this paper

Shrivastava, N., Tyagi, V. (2015). Region Based Image Retrieval Using Integrated Color, Texture and Shape Features. In: Mandal, J., Satapathy, S., Kumar Sanyal, M., Sarkar, P., Mukhopadhyay, A. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 340. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2247-7_32

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-2247-7_32

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2246-0

  • Online ISBN: 978-81-322-2247-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics