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An Efficient Method of Improving Image Retrieval Using Combined Global and Local Features

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Advances in Ubiquitous Networking 2 (UNet 2016)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 397))

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Abstract

Nowadays, with the increased use of digital images it has become essential to find an efficient system for searching and indexing of images from large image collections. CBIR systems can be used for searching and retrieving different kinds of images from large databases on the bases of the visual content of the images. Currently, CBIR techniques work on combination of low level features i.e. color, shape and texture. In this paper we have designed a content based image retrieval system based on the combination of local and global features. The local features are obtained through local binary pattern (LBP) technique which is used to extract texture-based features from an image, while the global features are extracted using Angular Radial Transform (ART). To demonstrate the efficacy of this combination, experiments are conducted on Columbia Object Image Li-brary (COIL-100) and MPEG-7 shape-1 part B database. The result showed significant improvement in the retrieval accuracy when compared to the existing system.

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Authors and Affiliations

  1. Department of Computer Science, Chouaib Doukkali University, El Jadida, Morocco

    Abderrahim Khatabi & Amal Tmiri

  2. Department of Mathematics, Chouaib Doukkali University, El Jadida, Morocco

    Ahmed Serhir

Authors
  1. Abderrahim Khatabi
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  2. Amal Tmiri
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  3. Ahmed Serhir
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Corresponding author

Correspondence to Abderrahim Khatabi .

Editor information

Editors and Affiliations

  1. Computer Science Laboratory (LIA), University of Avignon, Avignon, France

    Rachid El-Azouzi

  2. Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

    Daniel Sadoc Menasche

  3. Hassan II University of Casablanca, ENSEM, Casablanca, Morocco

    Essaïd Sabir

  4. CREATE-NET, Trento, Italy

    Francesco De Pellegrini

  5. INPT, Rabat, Morocco

    Mustapha Benjillali

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Khatabi, A., Tmiri, A., Serhir, A. (2017). An Efficient Method of Improving Image Retrieval Using Combined Global and Local Features. In: El-Azouzi, R., Menasche, D.S., Sabir, E., De Pellegrini, F., Benjillali, M. (eds) Advances in Ubiquitous Networking 2. UNet 2016. Lecture Notes in Electrical Engineering, vol 397. Springer, Singapore. https://doi.org/10.1007/978-981-10-1627-1_34

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  • DOI: https://doi.org/10.1007/978-981-10-1627-1_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1626-4

  • Online ISBN: 978-981-10-1627-1

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