Abstract
In this contribution we present a novel approach to the problem of color image indexing and retrieval. The indexing technique is based on the Gaussian Mixture modeling of the histogram of weights provided by the bilateral filtering scheme. In this way the proposed technique considers not only the global distribution of the color pixels comprising the image but also takes into account their spatial arrangement. The model parameters serve as signatures which enable fast and efficient color image retrieval. We show that the proposed approach is robust to color image distortions introduced by lossy compression artifacts and therefore it is well suited for indexing and retrieval of Internet based collections of color images.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Dempster, A., Laird, N., Rubin, D.: Maximum likelihood from incomplete data. Journal of the Royal Statistics Society 39, 1–38 (1977)
Jeong, S., Won, C.S., Gray, R.M.: Image retrieval using color histograms generated by Gauss mixture vector quantization. Computer Vision and Image Understanding 94(1-3), 44–66 (2004)
Kuo, W.J., Chang, R.F.: Approximating the statistical distribution of color histogram for content-based image retrieval. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 4, pp. 2007–2010 (2000)
Łuszczkiewicz, M., Smołka, B.: Gaussian mixture model based retrieval technique for lossy compressed color images. In: Kamel, M.S., Campilho, A. (eds.) ICIAR 2007. LNCS, vol. 4633, pp. 662–673. Springer, Heidelberg (2007)
Łuszczkiewicz, M., Smołka, B.: A robust indexing and retrieval method for lossy compressed color images. In: Proceedings of the IEEE International Symposium on Image and Signal Processing and Analysis, pp. 304–309 (2007)
Paris, S., Durand, F.: A fast approximation of the bilateral filter using a signal processing approach. International Journal of Computer Vision 39, 1–38 (2007)
Paulus, D., Horecki, K., Wojciechowski, K.: Localization of colored objects. In: Proceedings of International Conference on Image Processing, Vancouver, Canada, pp. 492–495 (2000)
Pioch, N.: Web museum, http://www.ibiblio.org/wm/ (1.03.2008)
Rubner, Y., Tomasi, C., Guibas, L.J.: A metric for distributions with applications to image databases. In: Proceedings of International Conference on Computer Vision, pp. 59–66 (1998)
Walczak, K.: Image retrieval using spatial color information. In: Skarbek, W. (ed.) CAIP 2001. LNCS, vol. 2124, pp. 53–60. Springer, Heidelberg (2001)
Wang, J.Z., Li, J., Wiederhold, G.: SIMPLIcity: semantics-sensitive integrated matching for picture libraries. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(9), 947–963 (2001)
Akaike, H.: A new look at the statistical model identification. IEEE Transactions on Automatic Control 19, 716–723 (1974)
van Berendonck, C., Jacobs, T.: Bubbleworld: A new visual information retreival technique. In: Pattison, T., Thomas, B. (eds.) Proceedings of the Australian Symposium on Information Visualisation, vol. 24, pp. 47–56. ACS, Adelaide (2003)
Bilmes, J.: A gentle tutorial on the EM algorithm and its application to parameter estimation for Gaussian mixture and Hidden Markov Models. Tech. Rep. ICSI-TR-97-021, University of Berkeley (1997)
Hitchcock, F.L.: The distribution of a product from several sources to numerous localities. Journal of Mathematical Physics 23(20), 224–230 (1941)
Hsu, W., Chua, T.S., Pung, H.K.: An integrated color-spatial approach to content-based image retrieval. In: Proceedings of ACM Multimedia Conference, pp. 305–313 (1995)
Huang, J., Kumar, S.R., Mitra, M., Zhu, W.J., Zabih, R.: Image indexing using color correlograms. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 762–768 (1997)
Lei, X., Jordan, M.: On convergence properties of the EM algorithm for Gaussian mixtures. Neural Computation 8(1), 129–151 (1996)
Niblack, W., Barber, R.: The QBIC project: Querying images by content, using color, texture, and shape. In: Proceedings of SPIE: Storage and Retrieval for Image and Video Databases, pp. 173–187 (1993)
Pentland, A., Picard, R.W., Sclaroff, S.: Photobook: Tools for content-based manipulation of image databases. In: Proceedings of SPIE: Storage and Retrieval for Image and Video Databases, pp. 34–47 (1994)
Rabiner, L., Juang, B.H.: Fundamentals of Speech Recognition. Prentice Hall PTR, Englewood Cliffs (1993)
Rachev, S.T.: The Monge-Kantorovich mass transference problem and its stochastic applications. Theory of Probability and its Applications 4(XXIX), 647–676 (1984)
Redner, R., Walker, H.: Mixture densities, maximum likelihood and the EM algorithm. SIAM Review 26(2), 195–239 (1984)
Schwarz, G.: Estimating the dimension of a model. The Annals of Statistics 6(2), 461–464 (1978)
Smith, J., Chang, S.F.: Tools and techniques for color image retrieval. In: Proceedings of SPIE: Storage and Retrieval for Image and Video Databases, pp. 426–437 (1996)
Smołka, B., Szczepański, M., Lukac, R., Venetsanoloulos, A.: Robust color image retrieval for the World Wide Web. In: Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, pp. 461–464 (2004)
Swain, M.J., Ballard, D.H.: Color indexing. International Journal on Compututer Vision 7(1), 11–32 (1991)
Wu, J.: On the convergence properties of the EM algorithm. The Annals of Statistics 11(1), 95–103 (1983)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Łuszczkiewicz, M., Smołka, B. (2009). Spatial Color Distribution Based Indexing and Retrieval Scheme. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds) Man-Machine Interactions. Advances in Intelligent and Soft Computing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00563-3_44
Download citation
DOI: https://doi.org/10.1007/978-3-642-00563-3_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00562-6
Online ISBN: 978-3-642-00563-3
eBook Packages: EngineeringEngineering (R0)