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International Conference Image Analysis and Recognition

ICIAR 2018: Image Analysis and Recognition pp 269–277Cite as

Saliency-Based Image Object Indexing and Retrieval

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10882))

Abstract

We suggest a novel approach to combine visual saliency model and object recognition to provide a more semantic description of an image based on human attention priority. The idea is to index and retrieve semantically more relevant images utilizing human saliency. Based on that, we developed a content-based image indexing and retrieval system. The resultant indexing and retrieval system works, though there is room for improvement in performance. We suggest the reasons and the possibilities for further improvements to develop a practical CBIR system.

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Author information

Authors and Affiliations

  1. Norwegian University of Science and Technology, 2815, Gjøvik, Norway

    Yat Hong Jacky Lam & Sule Yildirim Yayilgan

Authors
  1. Yat Hong Jacky Lam
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  2. Sule Yildirim Yayilgan
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Corresponding author

Correspondence to Yat Hong Jacky Lam .

Editor information

Editors and Affiliations

  1. University of Porto, Porto, Portugal

    Aurélio Campilho

  2. University of Waterloo, Waterloo, Ontario, Canada

    Fakhri Karray

  3. Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands

    Bart ter Haar Romeny

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Jacky Lam, Y.H., Yildirim Yayilgan, S. (2018). Saliency-Based Image Object Indexing and Retrieval. In: Campilho, A., Karray, F., ter Haar Romeny, B. (eds) Image Analysis and Recognition. ICIAR 2018. Lecture Notes in Computer Science(), vol 10882. Springer, Cham. https://doi.org/10.1007/978-3-319-93000-8_31

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  • DOI: https://doi.org/10.1007/978-3-319-93000-8_31

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92999-6

  • Online ISBN: 978-3-319-93000-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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