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Knowledge and Systems Engineering pp 233–245Cite as

Improving Text-Based Image Search with Textual and Visual Features Combination

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Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 326)

Abstract

With the huge number of available images on the web, an effective image retrieval system has been more and more needed. Improving the performance is one of crucial tasks in modern text-based image retrieval systems such as Google Image Search, Frickr, etc. In this paper, we propose a unified framework to cluster and re-rank returned images with respect to an input query. However, owning to a difference to previous methods of using only either textual or visual features of an image, we combine the textual and visual features to improve search performance. The experimental results show that our proposed model can significantly improve the performance of a text-based image search system (i.e. Flickr). Moreover, the performance of the system with the combination of textual and visual features outperforms the performance of both the textual-based system and the visual-based system.

Keywords

  • Image search system
  • Meta-search engine
  • Textual features
  • Visual features
  • Re-ranking
  • Clustering

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  • DOI: 10.1007/978-3-319-11680-8_19
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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Kyungpook National University, Daegu, Korea

    Xuan-Son Vu

  2. The Open University, Milton Keynes, UK

    Thanh Vu

  3. KTLab, University of Engineering and Technology (VNU-UET), Vietnam National University, Hanoi (VNUH), Ha Noi, Viet Nam

    Huong Nguyen & Quang-Thuy Ha

Authors
  1. Xuan-Son Vu
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  2. Thanh Vu
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  3. Huong Nguyen
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  4. Quang-Thuy Ha
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Corresponding author

Correspondence to Xuan-Son Vu .

Editor information

Editors and Affiliations

  1. Faculty of Information Technology, VNU University of Engineering and Technology, Hanoi, Vietnam

    Viet-Ha Nguyen

  2. Faculty of Information Technology, VNU University of Engineering and Technology, Hanoi, Vietnam

    Anh-Cuong Le

  3. School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Van-Nam Huynh

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Vu, XS., Vu, T., Nguyen, H., Ha, QT. (2015). Improving Text-Based Image Search with Textual and Visual Features Combination. In: Nguyen, VH., Le, AC., Huynh, VN. (eds) Knowledge and Systems Engineering. Advances in Intelligent Systems and Computing, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-319-11680-8_19

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  • DOI: https://doi.org/10.1007/978-3-319-11680-8_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11679-2

  • Online ISBN: 978-3-319-11680-8

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