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Online Visualisation of Google Images Results

  • Gerald Schaefer
  • David Edmundson
  • Shao Ying Zhu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8210)

Abstract

Visual information, especially in the form of images, is becoming increasingly important, and consequently there is a rising demand for effective tools to perform online image search. However, image search engines such as Google Images, are based on the text surrounding the images rather than the images themselves. At the same time, while the employed keyword-based search provides a basic level of filtering, it is not sufficient to handle large search results. Image database visualisation, which provides a visual overview of an image collection, could be applied to the retrieved images, but the associated overheads, both in terms of bandwidth and computational complexity, are prohibitive.

In this paper, we introduce an image browsing system that does not suffer from these drawbacks. In particular, we construct an interactive image database navigation application that uses the Huffman tables available in the JPEG headers of Google Images thumbnails directly as image features, and projects images onto a 2-dimensional visualisation space based on principal component analysis derived from the Huffman entries. Images are dynamically placed into a grid structure and organised in a tree-like hierarchy for visual browsing. Since we utilise information only from the JPEG header, the requirement in terms of bandwidth is very low, while no explicit feature calculation needs to be performed, thus allowing for interactive browsing of online image search results.

Keywords

image databases content-based image retrieval image browsing Google Images 

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References

  1. 1.
    Bartolini, I., Ciaccia, P., Patella, M.: Adaptively browsing image databases with PIBE. Multimedia Tools and Applications 31(3), 269–286 (2006)CrossRefGoogle Scholar
  2. 2.
    Datta, R., Joshi, D., Li, J., Wang, J.Z.: Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys 40(2), 1–60 (2008)CrossRefGoogle Scholar
  3. 3.
    Dontcheva, M., Agrawala, M., Cohen, M.: Metadata visualization for image browsing. In: 18th Annual ACM Symposium on User Interface Software and Technology (2005)Google Scholar
  4. 4.
    Edmundson, D., Schaefer, G.: Efficient and effective online image retrieval. In: IEEE Int. Conference on Systems, Man, and Cybernetics (2012)Google Scholar
  5. 5.
    Edmundson, D., Schaefer, G.: Fast JPEG image retrieval using optimised Huffman tables. In: 21st Int. Conference on Pattern Recognition, pp. 3188–3191 (2012)Google Scholar
  6. 6.
    Gomi, A., Miyazaki, R., Itoh, T., Li, J.: CAT: A hierarchical image browser using a rectangle packing technique. In: 12th Int. Conference on Information Visualization, pp. 82–87 (2008)Google Scholar
  7. 7.
    Heesch, D.: A survey of browsing models for content based image retrieval. Multimedia Tools and Applications 40(2), 261–284 (2008)CrossRefGoogle Scholar
  8. 8.
    Heesch, D., Rüger, S.: NNk networks for content-based image retrieval. In: European Conference on Information Retrieval, pp. 253–266 (2004)Google Scholar
  9. 9.
    Keller, I., Meiers, T., Ellerbrock, T., Sikora, T.: Image browsing with PCA-assisted user-interaction. In: IEEE Workshop on Content-Based Access of Image and Video Libraries, pp. 102–108 (2001)Google Scholar
  10. 10.
    Liu, H., Xie, X., Tang, X., Li, Z.W., Ma, W.Y.: Effective browsing of web image search results. In: ACM Int.l Workshop on Multimedia Information Retrieval, pp. 84–90 (2004)Google Scholar
  11. 11.
    Moghaddam, B., Tian, Q., Lesh, N., Shen, C., Huang, T.S.: Visualization and user-modeling for browsing personal photo libraries. Int. Journal of Computer Vision 56(1-2), 109–130 (2004)CrossRefGoogle Scholar
  12. 12.
    Nguyen, G.P., Worring, M.: Interactive access to large image collections using similarity-based visualization. Journal of Visual Languages and Computing 19(2), 203–224 (2008)CrossRefGoogle Scholar
  13. 13.
    Plant, W., Schaefer, G.: Navigation and browsing of image databases. In: Int. Conference on Soft Computing and Pattern Recognition, pp. 750–755 (2009)Google Scholar
  14. 14.
    Plant, W., Schaefer, G.: Visualising image databases. In: IEEE Int. Workshop on Multimedia Signal Processing, pp. 1–6 (2009)Google Scholar
  15. 15.
    Plant, W., Schaefer, G.: Visualisation and browsing of image databases. In: Lin, W., Tao, D., Kacprzyk, J., Li, Z., Izquierdo, E., Wang, H. (eds.) Multimedia Analysis, Processing and Communications. SCI, vol. 346, pp. 3–57. Springer, Heidelberg (2011)Google Scholar
  16. 16.
    Plant, W., Schaefer, G.: Interactive exmploration of large remote image databases. In: 20th ACM Int. Conference on Multimedia (2012)Google Scholar
  17. 17.
    Rodden, K.: Evaluating Similarity-Based Visualisations as Interfaces for Image Browsing. PhD thesis, University of Cambridge Computer Laboratory (2001)Google Scholar
  18. 18.
    Rubner, Y., Guibas, L., Tomasi, C.: The earth mover’s distance, multi-dimensional scaling, and color-based image retrieval. In: Image Understanding Workshop, pp. 661–668 (1997)Google Scholar
  19. 19.
    Schaefer, G.: A next generation browsing environment for large image repositories. Multimedia Tools and Applications 47(1), 105–120 (2010)CrossRefGoogle Scholar
  20. 20.
    Schaefer, G.: Interacting with image collections – Visualisation and browsing of image repositories. In: 20th ACM Int. Conference on Multimedia (2012)Google Scholar
  21. 21.
    Schaefer, G., Ruszala, S.: Image database navigation on a hierarchical MDS grid. In: Franke, K., Müller, K.-R., Nickolay, B., Schäfer, R. (eds.) DAGM 2006. LNCS, vol. 4174, pp. 304–313. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  22. 22.
    Schaefer, G., Stich, M.: UCID - An Uncompressed Colour Image Database. In: Storage and Retrieval Methods and Applications for Multimedia. Proceedings of SPIE, vol. 5307, pp. 472–480 (2004)Google Scholar
  23. 23.
    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 Analysis and Machine Intelligence 22(12), 1249–1380 (2000)CrossRefGoogle Scholar
  24. 24.
    Wallace, G.K.: The JPEG still picture compression standard. Communications of the ACM 34(4), 30–44 (1991)CrossRefGoogle Scholar
  25. 25.
    Worring, M., de Rooij, O., van Rijn, T.: Browsing visual collections using graphs. In: Int. Workshop on Workshop on Multimedia Information Retrieval, pp. 307–312 (2007)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Gerald Schaefer
    • 1
  • David Edmundson
    • 1
  • Shao Ying Zhu
    • 2
  1. 1.Department of Computer ScienceLoughborough UniversityLoughboroughU.K.
  2. 2.School of Computing and MathematicsUniversity of DerbyDerbyU.K.

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