A weighted dominant color descriptor for content-based image retrieval

  • Authors:

  • Ahmed Talib;Massudi Mahmuddin;Husniza Husni;Loay E. George

  • Affiliations:

  • Computer Science Dept., School of Computing, University Utara Malaysia, 06010 Sintok, Kedah, Malaysia and IT Dept., Technical College of Management, Foundation of Technical Education, 10047 Bab Al ...;Computer Science Dept., School of Computing, University Utara Malaysia, 06010 Sintok, Kedah, Malaysia;Computer Science Dept., School of Computing, University Utara Malaysia, 06010 Sintok, Kedah, Malaysia;Computer Science Dept., College of Science, Baghdad University, 10071 Al-Jadriya, Baghdad, Iraq

  • Venue:
  • Journal of Visual Communication and Image Representation
  • Year:
  • 2013

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Abstract

Color has been extensively used in the process of image retrieval. The dominant color descriptor (DCD) that was proposed by MPEG-7 is a famous case in point. It is based on compactly describing the prominent colors of an image or a region. However, this technique suffers from some shortcomings; especially with respect to object-based image retrieval. In this paper, a new semantic feature extracted from dominant colors (weight for each DC) is proposed. The newly proposed technique helps reduce the effect of image background on image matching decision where an object's colors receive much more focus. In addition, a modification to DC-based similarity measure is also proposed. Experimental results demonstrate that the proposed descriptor with the similarity measure modification performs better than the existing descriptor in content-based image retrieval application. The proposed descriptor considers as step forward to the object-based image retrieval.