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An efficient image retrieval method using adaptive weights

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Abstract

In existing image retrieval systems using a multipoint query, the neighborhood of the various optimal query points is determined in the same way. The different nature of the various optimal query points was not taken into consideration. This approach confines the performance of the system. To overcome this confinement, in this paper, we propose an image retrieval method through adaptive weights (Aweight) which is possible to compute the various optimal query points, optimal weights and improved distance functions to improve accuracy. In addition, our method constructs clusters without re-clustering the whole feedback image set. The experiments were performed on a set of 10,800 images and the results demonstrate that the proposed method improves performance of system in terms of accuracy.

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Acknowledgments

The author gratefully acknowledges the many helpful suggestions of the anonymous reviewers during the preparation of the paper. This research was supported by the “Research on image retrieval based on multi queries” under grant no.PTNTŁD .17.04, and by the key laboratory Network Technology and Multimedia, Institute of Information Technology, Vietnam Academy of Science and Technology. The authors express their gratitude to Dr. Can Nguyen Van for supporting the financial part of this article.

Author information

Authors and Affiliations

  1. Information Technology Faculty, Electric Power University, Hanoi, Viet Nam

    Quynh Nguyen Huu & Canh Phuong Van

  2. Thai Nguyen University of Science, Quyet Thang, Thai Nguyen, Viet Nam

    Quynh Dao Thi Thuy

  3. The People’s Police University of Technology and Logistic, Thuan Thanh, Viet Nam

    Can Nguyen Van

  4. Institute of Information Technology, Vietnam Academy of Science and Technology, Hanoi, Viet Nam

    Tao Ngo Quoc

Authors
  1. Quynh Nguyen Huu
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  2. Quynh Dao Thi Thuy
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  3. Canh Phuong Van
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  4. Can Nguyen Van
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  5. Tao Ngo Quoc
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Corresponding author

Correspondence to Quynh Dao Thi Thuy.

Appendices

Appendix A

The average accuracy of the AWEIGHT method in each of the 80 categories

Table 2 The average accuracy of the AWEIGHT method in each of the 80 categories with three iterations
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Appendix B

The retrieval interface with the initial query image that has ID 84025 of the category pl_flower in the Corel Photo Gallery

Fig. 14
figure 14

The resulting interface implements the initial query. The result set contains 40 retrieved relevant images over 100 retrieved images

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Fig. 15
figure 15

The top results after one feedback iteration for the initial query. The result set contains 77 retrieved relevant images over 100 retrieved images (Images with red borders in Figs. 14, 15, 16 and 17 imply the same category art_dino with the query image)

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Fig. 16
figure 16

The top results after two feedback iterations for the initial query. The result set contains 86 retrieved relevant images over 100 retrieved images

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Fig. 17
figure 17

The top results after three feedback iterations for the initial query. The result set contains 100 retrieved relevant images over 100 retrieved images

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Huu, Q.N., Thuy, Q.D.T., Phuong Van, C. et al. An efficient image retrieval method using adaptive weights. Appl Intell 48, 3807–3826 (2018). https://doi.org/10.1007/s10489-018-1174-6

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  • DOI: https://doi.org/10.1007/s10489-018-1174-6

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