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Parametric approach to the retrieval of lossy compressed color images

  • Silesian University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The rapid development of the Internet in the early 1990s caused an explosive growth of publicly accessible multimedia resources. It created new viewpoint on storage, distribution and processing of enormous collections of images. Along with the development of the World Wide Web there is much effort dedicated to create a content-based image retrieval systems which are able to efficiently index, retrieve and manage large scale databases. In this paper we propose a color indexing method based on the Gaussian Mixture Model of color histograms. The model parameters serve as signatures enabling fast and efficient color image retrieval. In this paper 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 stored in lossy compression formats.

Original languageEnglish
Title of host publicationPhotonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2007
DOIs
Publication statusPublished - 2008
EventPhotonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2007 - Wilga, Poland
Duration: 21 May 200727 May 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6937
ISSN (Print)0277-786X

Conference

ConferencePhotonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2007
Country/TerritoryPoland
CityWilga
Period21/05/0727/05/07

Keywords

  • Color histogram
  • Color image
  • Gaussian mixture model
  • Image retrieval
  • Lossy compression

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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