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An Innovative Multiple-Object Image Retrieval Framework Using Hierarchical Region Tree

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  • Wei-Bang Chen

    (Department of Mathematics and Computer Science, Virginia State University, Petersburg, VA, USA)

  • Chengcui Zhang

    (Department of Computer and Information Sciences, University of Alabama at Birmingham, Birmingham, AL, USA)

Abstract

Inaccurate image segmentation often has a negative impact on object-based image retrieval. Researchers have attempted to alleviate this problem by using hierarchical image representation. However, these attempts suffer from the inefficiency in building the hierarchical image representation and the high computational complexity in matching two hierarchically represented images. This paper presents an innovative multiple-object retrieval framework named Multiple-Object Image Retrieval (MOIR) on the basis of hierarchical image representation. This framework concurrently performs image segmentation and hierarchical tree construction, producing a hierarchical region tree to represent the image. In addition, an efficient hierarchical region tree matching algorithm is designed for multiple-object retrieval with a reasonably low time complexity. The experimental results demonstrate the efficacy and efficiency of the proposed approach.

Suggested Citation

  • Wei-Bang Chen & Chengcui Zhang, 2013. "An Innovative Multiple-Object Image Retrieval Framework Using Hierarchical Region Tree," International Journal of Multimedia Data Engineering and Management (IJMDEM), IGI Global, vol. 4(3), pages 1-23, July.
    • Handle: RePEc:igg:jmdem0:v:4:y:2013:i:3:p:1-23
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