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Semantic-Based Image Retrieval Using \(R^S\)-Tree and Neighbor Graph

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Information Systems and Technologies (WorldCIST 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 469))

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Abstract

In this paper, we present a semantic-based image retrieval method using \(R^S\)-Tree structure and neighbor graph. The main ideas of the paper include (1) proposing a structure by combining of \(R^S\)-Tree and neighbor clustering graph, named NBGraphRST; (2) enriching an ontology framework to describe the semantic feature of images. Firstly, a query image is extracted as a low-level visual feature vector and retrieved on NBGraphRST to get a set of content-based similar images. Secondly, the input images are classified by the k-nearest neighbor (k-NN) method to create a set of visual vocabularies. Finally, the SPARQL query is generated to retrieve the semantics of similar images based on ontology. On the basis of the proposed method, the experiment is performed on data-sets COREL, Wang, Oxford Flowers-17.

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Acknowledgment

The authors would like to thank the Faculty of Information Technology, Universi-ty of Sciences - Hue University for their professional advice for this study. We would also like to thank HCMC University of Food Industry, Ba Ria - Vung Tau University, University of Education HCMC, and research group SBIR HCM, which are sponsors of this research. We also would like to express our sincere thanks to reviewers for their helpful comments on this article.

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Authors and Affiliations

  1. University of Sciences - Hue University, Hue, Vietnam

    Le Thi Vinh Thanh & Le Manh Thanh

  2. HCMC University of Education, Ho Chi Minh City, Vietnam

    Van The Thanh

  3. Ba Bia - Vung Tau University, Ba Ria - Vung Tau City, Vietnam

    Le Thi Vinh Thanh

Authors
  1. Le Thi Vinh Thanh
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  2. Le Manh Thanh
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  3. Van The Thanh
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Corresponding author

Correspondence to Van The Thanh .

Editor information

Editors and Affiliations

  1. ISEG, Universidade de Lisboa, Lisboa, Portugal

    Alvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. Institute of Data Science and Digital Te, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda

  4. DCT, Universidade Portucalense, PORTO, Portugal

    Fernando Moreira

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Thanh, L.T.V., Thanh, L.M., Thanh, V.T. (2022). Semantic-Based Image Retrieval Using \(R^S\)-Tree and Neighbor Graph. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F. (eds) Information Systems and Technologies. WorldCIST 2022. Lecture Notes in Networks and Systems, vol 469. Springer, Cham. https://doi.org/10.1007/978-3-031-04819-7_18

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