Skip to main content
SpringerLink
Log in

Semantic Relationship-Based Image Retrieval Using KD-Tree Structure

  • Conference paper
  • First Online:
Intelligent Information and Database Systems (ACIIDS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13757))

Included in the following conference series:

Abstract

The semantic relationship of visual objects plays an important role in determining the context and semantics of an image. In this paper, a method of classifying semantic relationships between objects on image is proposed and applied to a semantic-based image retrieval system. Firstly, the visual objects on an input image are extracted and classified using the R-CNN network model. Secondly, a semantic description of the image is determined by the KD-Tree structure. From that, a model of classifying semantic relationships and extracting semantic descriptions for an input image is proposed to retrieve a set of similar images by semantics. To prove the correctness of the proposed theoretical basis, an experiment was built on the COCO and Flickr image data sets with an average image retrieval performance of 0.6972, and 0.7794, respectively. Experimental results are compared with other works on the same data set to demonstrate the effectiveness of our proposed method and can be applied to multi-object image data sets.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Chen, S., Li, Z., Tang, Z.: Relation R-CNN A graph based relation-aware network for object detection. IEEE Signal Process. Lett. 27, 1680–1684 (2020)

    Article  Google Scholar 

  2. Dinh, N.T., Van Thanh, T., Thanh, L.M.: A method of image classification base on kd-tree structure for semantic-based image retrieval system. In: Proceedings of the National Conference on Basic Research and IT Applications (FAIR21) (2021). ISBN 978-604-9988-60-8

    Google Scholar 

  3. https://cocodataset.org/download

  4. https://www.kaggle.com/datasets/hsankesara/flickr-image-datas

  5. Kuznetsova, A., et al.: The open images dataset v4. Int. J. Comput. Vision 128(7), 1956–1981 (2020)

    Article  Google Scholar 

  6. Zhang, Y., et al.: Fast face sketch synthesis via kd-tree search. In: European Conference on Computer Vision. Springer, Cham (2016)

    Google Scholar 

  7. Wang, Z., Liu, X., Li, H., Sheng, L., Yan, J., Wang, X., Shao, J.: Camp Cross-modal adaptive message passing for text-image retrieval. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 5764–5773 (2019)

    Google Scholar 

  8. Nhi, N.T.U., Le, T.M.: A model of semantic-based image retrieval using C-tree and neighbor graph. Int. J. Semant. Web Inf. Syst. (IJSWIS) 18(1), 1–23 (2022)

    Article  Google Scholar 

  9. He, K., Gkioxari, G., Dollár, P., Girshick, R.: Mask R-CNN. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2961–2969 (2017)

    Google Scholar 

  10. Nguyen, T.D., Van, T.T., Le, M.T.: Image classification using KdTree for image retrieval problem. J. Res. Dev. Inf. Coommun. Technol. 1, 33–44 (2021)

    Google Scholar 

  11. Schroeder, B., Tripathi, S.: Structured query-based image retrieval using scene graphs. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 178–179 (2020)

    Google Scholar 

  12. Bentley Jon Louis: Multidimensional binary search trees used for associative searching. Commun. ACM 18(9), 509–517 (1975)

    Article  MATH  Google Scholar 

  13. Yoon, S., et al.: Image-to-image retrieval by learning similarity between scene graphs, arXiv preprint arXiv, 4322, 2012.14700 (2020)

    Google Scholar 

  14. Icarte, R.T., Baier, J.A., Ruz, C., Soto, A.: How a general-purpose commonsense ontology can improve performance of learning-based image retrieval. arXiv preprint arXiv, 1705–08844 (2017)

    Google Scholar 

  15. Hou, W., Li, D., Xu, C., Zhang, H., Li, T.: An advanced k nearest neighbor classification algorithm based on KD-tree. In: IEEE International Conference of Safety Produce Informatization (IICSPI) (2018)

    Google Scholar 

  16. Lee, H., Eum, S., Kwon, H.: Me R-CNN: multi-expert R-CNN for object detection. IEEE Trans. Image Process. 29, 1030–1044 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  17. Cai, Z., Vasconcelos, N.: Cascade R-CNN: delving into high quality object detection. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6154–6162 (2018)

    Google Scholar 

  18. Dinh, N. T., and Le, T. M.: An Improvement Method of Kd-Tree Using k-Means and k-NN for Semantic-Based Image Retrieval System. In: World Conference on Information Systems and Technologies, pp. 177–187. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-04819-7_19

Download references

Acknowledgment

The authors would like to thank the Faculty of Information Technology, Univer-sity of Science - Hue University for their professional advice for this study. We would also like to thank HCMC University of Food Industry, HCMC University of Education, and research group SBIR-HCM, which are sponsors of this re-search.

Author information

Authors and Affiliations

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

    Nguyen Thi Dinh & Thanh Manh Le

  2. University of Food Industry, HoChiMinh city, Vietnam

    Nguyen Thi Dinh

  3. HCMC University of Education, HoChiMinh city, Vietnam

    Thanh The Van

Authors
  1. Nguyen Thi Dinh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thanh The Van
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Thanh Manh Le
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Thanh Manh Le .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Vietnam National University, Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Tien Khoa Tran

  3. Al-Farabi Kazakh National University, Almaty, Kazakhstan

    Ualsher Tukayev

  4. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  6. University of Newcastle, Newcastle, NSW, Australia

    Edward Szczerbicki

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dinh, N.T., Van, T.T., Le, T.M. (2022). Semantic Relationship-Based Image Retrieval Using KD-Tree Structure. In: Nguyen, N.T., Tran, T.K., Tukayev, U., Hong, TP., Trawiński, B., Szczerbicki, E. (eds) Intelligent Information and Database Systems. ACIIDS 2022. Lecture Notes in Computer Science(), vol 13757. Springer, Cham. https://doi.org/10.1007/978-3-031-21743-2_36

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-21743-2_36

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21742-5

  • Online ISBN: 978-3-031-21743-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation