Skip to main content
SpringerLink
Log in

An efficient signature representation for retrieval of spatially similar images

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

Multimedia applications involving image retrieval demand fast and efficient response. Efficiency of search and retrieval of information in a database system is index dependent. Generally, a two-level indexing scheme in an image database can help to reduce the search space against a given query image. In such type of indexing scheme, the first level is required to significantly reduce the search space for second stage of comparisons and must be computationally efficient. It is also required to guarantee that no false negatives may result. The second level of indexing involves more detailed analysis and comparison of potentially relevant images. In this paper, we present an efficient signature representation scheme for first level of a two-level image indexing scheme that is based on hierarchical decomposition of image space into spatial arrangement of image features. Experimental results demonstrate that our signature representation scheme results in fewer number of matching signatures in the first level and significantly improves the overall computational time. As this scheme relies on corner points as the salient feature points in an image to describe its contents, we also compare results using several different contemporary corner detection methods. Further, we formally prove that the proposed signature representation scheme not only results in fewer number of signatures but also does not result in any false negative.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Ahmad I., Grosky W.I.: Indexing and retrieval of images by spatial constraints. J. Vis. Commun. Image R. 14(3), 291–320 (2003)

    Article  Google Scholar 

  2. Berreti S., Bimbo A.D., Pala P.: Retrieval by shape similarity with perceptual distance and effective indexing. IEEE Trans. Multimed. 2(4), 225–239 (2000)

    Article  Google Scholar 

  3. Berreti S., Bimbo A.D., Vicario E.: Weighted walkthroughs between extended entities for retrieval by spatial arrangement. IEEE Trans. Multimed. 5(1), 52–70 (2003)

    Article  Google Scholar 

  4. Chang C., Wu T.: An exact match retrieval scheme based upon principal component analysis. Pattern Recogn. Lett. 16(5), 465–470 (1995)

    Article  MathSciNet  Google Scholar 

  5. Chang S.K., Shi Q.Y., Yan C.W.: Iconic indexing by 2-D strings. IEEE Trans. Pattern Anal. Mach. Intell. 9(3), 413–428 (1987)

    Article  Google Scholar 

  6. Chen, X., Ahmad, I.S.: Shape-based image retrieval using k-means clustering and neural networks. In: Proceedings of the IEEE Pacific-Rim Symposium on Image and Video Technology, pp. 893–904. Santiago, Chile (2007)

  7. Ciaccia, P., Patella, M., Zezula, P.: M-tree: an efficient access method for similarity search in metric spaces. In: Proceedigs of the 23rd International Conference on Very Large Data Bases, pp. 426–435. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (1997)

  8. Datta R., Joshi D., Wang J.: Image retrieval: ideas, influences, and trends of the new age. ACM Comput. Surv. 40(25), 1–560 (2008)

    Article  Google Scholar 

  9. Do M.N., Vetterli M.: Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance. IEEE Trans. Image Process. 11(2), 146–158 (2002)

    Article  MathSciNet  Google Scholar 

  10. Faloutsos C., Christodoulakis S.: Signature files: an access method for documents and its analytical performance evaluation. ACM Trans. Inf. Syst. 2(4), 267–288 (1984)

    Article  Google Scholar 

  11. Flickner M., Sawhney H., Niblack W., Ashley J., Huang Q., Dom B., Gorkani M., Hafner J., Lee D., Petkovic D., Steele D., Yanker P.: Query by image and video content: The QBIC system. Computer 28(9), 23–32 (1995)

    Article  Google Scholar 

  12. Gudivada V.: Θℜ-string: a geometry-based representation for efficient and effective retrieval of images by spatial similarity. IEEE Trans. Knowl. Data Eng. 10, 504–512 (1998)

    Article  Google Scholar 

  13. Gudivada V.N., Raghavan V.V.: Content-based image retrieval systems-guest editor’s introduction. Computer 28(9), 18–22 (1995)

    Article  Google Scholar 

  14. Guldogan E., Gabbouj M.: Feature selection for content-based image retrieval. Signal Image Video Process. 2(3), 241–250 (2008)

    Article  MATH  Google Scholar 

  15. Harris, C., Stephens, M.: A combined corner and edge detector. In: Proceedings of the Alvey Vision Conference, pp. 147–151 (1988)

  16. Hashizume, C.: Focused color intersection with efficient searching for object detection and image retrieval. In: Proceedings of the International Conference on Multimedia Computing and Systems, p. 0229. IEEE Computer Society, Washington, DC, USA (1996)

  17. Hoaglin D.C., Mosteller F., Tukey J.W.: Understanding Robust and Exploratory Data Analysis. Wiley, New York (1983)

    MATH  Google Scholar 

  18. Hsu F.J., Lee S.Y., Lin B.S.: 2D C-tree spatial representation for iconic image. J. Vis. Lang. Comput. 10(2), 147–164 (1999)

    Article  Google Scholar 

  19. Hu, W.C., Ritter, G.X.: A line string image representation for image storage and retrieval. In: Proceedigs of the IEEE International Conference on Multimedia Computing Systems, pp. 434–441 (1997)

  20. Huang P.W., Jean Y.R.: Using 2D C+-strings as spatial knowledge representation for image database systems. Pattern Recogn. 27(9), 1249–1257 (1994)

    Article  Google Scholar 

  21. Jungert, E., Chang, S.K.: An algebra for symbolic image manipulation and transformation. In: Proceedings of the IFIP TC 2/WG 2.6 Working Conference on Visual Database Systems, pp. 301–307 (1989)

  22. Khan, N.M., Ahmad, I.S.: A new signature for quadtree based image matching. In: Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia, pp. 20–27. Kuala Lumpur, Malaysia (2009)

  23. Kimia, B.: A large binary image database. Brown University, The Laboratory for Engineering Man/Machine Systems. http://www.lems.brown.edu/~dmc (2010)

  24. Latecki L.J., Lakämper R.: Shape similarity measure based on correspondence of visual parts. IEEE Trans. Pattern Anal. Mach. Intell. 22(10), 1185–1190 (2000)

    Article  Google Scholar 

  25. Lee S., Yang M., Chen J.: Signature file as a spatial filter for iconic image database. J. Vis. Lang. Comput. 3(4), 373–397 (1992)

    Article  MathSciNet  Google Scholar 

  26. Li J., Gray R.M., Olshen R.A.: Multiresolution image classification by hierarchical modeling with two dimensional hidden Markov models. IEEE Trans. Inf. Theory 46(5), 1826–1841 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  27. Manjunath B.S., Ohm J., Vasudevan V.V., Yamada A.: Color and texture descriptors. IEEE Trans. Circ. Syst. Video Technol. 11(6), 703–715 (2001)

    Article  Google Scholar 

  28. Mariscoi M.D., Cinque L., Levialdi L.: Indexing pictorial documents by their content: a survey of current techniques. Image Vision Comput. 15(2), 119–141 (1997)

    Article  Google Scholar 

  29. Natsev A., Rastogi R., Shim K.: WALRUS: a similarity retrieval algorithm for image databases. SIGMOD Rec. 28(2), 395–406 (1999)

    Article  Google Scholar 

  30. Petraglia G., Sebillo M., Tucci M., Tortora G.: Virtual images for similarity retrieval in image databases. IEEE Trans. Knowl. Data Eng. 13(6), 951–967 (2001)

    Article  Google Scholar 

  31. Petrakis E.G., Faloutsos C., Lin K.I.D.: Imagemap: an image indexing method based on spatial similarity. IEEE Trans. Knowl. Data Eng. 14(5), 979–987 (2002)

    Article  Google Scholar 

  32. Petrakis G., Diplaros A., Milios E.: Matching and retrieval of distorted and occluded shapes using dynamic programming. IEEE Trans. Pattern Anal. Mach. Intell. 24(11), 1501–1516 (2002)

    Article  Google Scholar 

  33. Pfaltz J.L., Berman W.J., Cagley E.M.: Partial-match retrieval using indexed descriptor files. Commun. ACM 23(9), 522–528 (1980)

    Article  MATH  MathSciNet  Google Scholar 

  34. Samet H.: Distance transform for images represented by quadtrees. IEEE Trans. Pattern Anal. Mach. Intell. 4(3), 298–303 (1982)

    Article  Google Scholar 

  35. Schmid C., Mohr R., Bauckhage C.: Evaluation of interest point detectors. Int. J. Comput. Vision 37(2), 151–172 (2000)

    Article  MATH  Google Scholar 

  36. Smith, J.R., Chang, S.: VisualSEEk: a fully automated content-based image query system. In: Proceedings of the 4th ACM international conference on Multimedia, pp. 87–98. ACM, New York, NY, USA (1996)

  37. Smith S.M., Brady J.M.: SUSAN—A new approach to low level image processing. Int. J. Comput. Vision 23(1), 45–78 (1997)

    Article  Google Scholar 

  38. Tuytelaars T., Mikolajczyk K.: Local invariant feature detectors: A survey. Found. Trends Comput. Graph. Vis. 3(3), 177–280 (2007)

    Article  Google Scholar 

  39. Vincent E., Laganire R.: Detecting and matching feature points. J. Vis. Commun. Image R. 16(1), 38–54 (2005)

    Article  Google Scholar 

  40. Wang, J.Z., Boujemaa, N., Bimbo, A.D., Geman, D., Hauptmann, A.G., Tesić, J.: Diversity in multimedia information retrieval research. In: Proceedings of the 8th ACM international workshop on Multimedia information retrieval, pp. 5–12. ACM, New York, NY, USA (2006)

  41. Wang Y.: Image indexing and similarity retrieval based on spatial relationship model. Inf. Sci. Inf. Comput. Sci. 154(1–2), 39–58 (2003)

    Google Scholar 

  42. Xing, N., Ahmad, I.S.: Shape-based image retrieval. In: Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia, pp. 543–547. Kuala Lumpur, Malaysia (2009)

  43. Yu H., Yang J.: A direct LDA algorithm for high-dimensional data with application to face recognition. Pattern Recogn. 34, 2067–2070 (2001)

    Article  MATH  Google Scholar 

  44. Zhang D., Lu G.: Shape-based image retrieval using generic fourier descriptor. Sig. Proc. Image Comm. 17(10), 825–848 (2002)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Science, University of Windsor, Windsor, ON, N9B 3P4, Canada

    Naimul Mefraz Khan & Imran Shafiq Ahmad

Authors
  1. Naimul Mefraz Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Imran Shafiq Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Naimul Mefraz Khan.

Additional information

Authors would like to acknowledge partial support provided by the University of Windsor and the Natural Science and Engineering Research Council (NSERC)—Canada.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Khan, N.M., Ahmad, I.S. An efficient signature representation for retrieval of spatially similar images. SIViP 6, 55–70 (2012). https://doi.org/10.1007/s11760-010-0179-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-010-0179-3

Keywords

Search

Navigation