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A Combination of Spatial Pyramid and Inverted Index for Large-Scale Image Retrieval

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  • Vinh-Tiep Nguyen

    (University of Science, Vietnam National University, Ho Chi Minh City, Vietnam)

  • Thanh Duc Ngo

    (University of Information Technology, Vietnam National University, Ho Chi Minh City, Vietnam)

  • Minh-Triet Tran

    (University of Science, Vietnam National University, Ho Chi Minh City, Vietnam)

  • Duy-Dinh Le

    (University of Information Technology, Vietnam National University, Ho Chi Minh City, Vietnam)

  • Duc Anh Duong

    (University of Information Technology, Vietnam National University, Ho Chi Minh City, Vietnam)

Abstract

Large-scale image retrieval has been shown remarkable potential in real-life applications. The standard approach is based on Inverted Indexing, given images are represented using Bag-of-Words model. However, one major limitation of both Inverted Index and Bag-of-Words presentation is that they ignore spatial information of visual words in image presentation and comparison. As a result, retrieval accuracy is decreased. In this paper, the authors investigate an approach to integrate spatial information into Inverted Index to improve accuracy while maintaining short retrieval time. Experiments conducted on several benchmark datasets (Oxford Building 5K, Oxford Building 5K+100K and Paris 6K) demonstrate the effectiveness of our proposed approach.

Suggested Citation

  • Vinh-Tiep Nguyen & Thanh Duc Ngo & Minh-Triet Tran & Duy-Dinh Le & Duc Anh Duong, 2015. "A Combination of Spatial Pyramid and Inverted Index for Large-Scale Image Retrieval," International Journal of Multimedia Data Engineering and Management (IJMDEM), IGI Global, vol. 6(2), pages 37-51, April.
    • Handle: RePEc:igg:jmdem0:v:6:y:2015:i:2:p:37-51
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