Color texture retrieval using hypercomplex wavelets

Fahad S. Al-Qadda, Lahouari Ghouti

Research output: Contribution to conferencePaperpeer-review

Abstract

In this paper, we propose a new algorithm for color texture retrieval by combining the feature extraction and similarity measurement tasks into a joint modeling and classification scheme based on the statistical representation of hypercomplex wavelets. The proposed statistical model leads to a new hypercomplex wavelet-based color texture retrieval method that is based on the accurate modeling of the marginal distribution of the hypecomplex wavelet coefficients using generalized Gaussian density (GGD) and on the existence a closed form for the Kullbak-Leibler distance (KLD) between GGDs. The efficiency of the proposed retrieval method is characterized by greater accuracy and flexibility in capturing the color texture information. Using a database of 640 color textures, the experimental results indicate that the proposed method significantly improves retrieval rates compared with traditional color approaches, while it enjoys a similar computational complexity.

Original languageEnglish
Pages121-126
Number of pages6
DOIs
StatePublished - 2009
Event2009 International Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2009 - Edinburgh, United Kingdom
Duration: 20 Aug 200922 Aug 2009

Conference

Conference2009 International Symposium on Bio-inspired, Learning, and Intelligent Systems for Security, BLISS 2009
Country/TerritoryUnited Kingdom
CityEdinburgh
Period20/08/0922/08/09

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Software

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