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Color-Based Pseudo Object Model for Image Retrieval with Relevance Feedback

  • Tat-Seng Chua
  • Chun-Xin Chu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1554)

Abstract

Color has been widely used in content-based image retrieval system. The problem with using color is that its representation is low level and hence its retrieval effectiveness is limited. This paper examines the issues related to improving the effectiveness of color-based image retrieval system. It explores the choice of suitable color space and color resolutions for representation and retrieval. This work also emphasizes the use of color coherent vector (CCV) as the basic model for retrieval. CCV is an extension of Color Histogram method to provide low-level representations of objects within the images. A relevance feedback (RF) technique is developed that uses the pseudo object information from relevant images to enhance subsequent retrieval performance. The overall system is tested on a large image database containing over 12,000 images. Tests were performed to evaluate the effectiveness of pseudo object based retrieval method with RF at a number of color resolutions. Results indicate that the RF method is effective and a medium color resolution of 316 colors performs the best.

Keywords

Color Space Image Retrieval Query Image Relevance Feedback Color Histogram 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Tat-Seng Chua
    • 1
  • Chun-Xin Chu
    • 1
  1. 1.School of ComputingNational University of SingaporeSingapore

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