Image Disorder Characterization Based on Rate Distortion

  • Claudia Iancu
  • Inge Gavat
  • Mihai Datcu
Conference paper

DOI: 10.1007/11881216_28

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4177)
Cite this paper as:
Iancu C., Gavat I., Datcu M. (2006) Image Disorder Characterization Based on Rate Distortion. In: Marín R., Onaindía E., Bugarín A., Santos J. (eds) Current Topics in Artificial Intelligence. CAEPIA 2005. Lecture Notes in Computer Science, vol 4177. Springer, Berlin, Heidelberg

Abstract

Rate distortion theory is one of the areas of information transmission theory with important applications in multimodal signal processing, as for example image processing, information bottleneck and steganalysis. This article present an image characterization method based on rate distortion analysis in the feature space. This space is coded using clustering as vector quantization (k-means). Since image information usually cannot be coded by single clusters, because there are image regions corresponding to groups of clusters, the rate and distortion are specifically defined. The rate distortion curve is analyzed, extracting specific features for implementing a database image classification system.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Claudia Iancu
    • 1
  • Inge Gavat
    • 1
  • Mihai Datcu
    • 2
  1. 1.”Politehnica” University BucharestRomania
  2. 2.German Aerospace Center DLRGermany

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