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A Novel Low Level Feature Normalization Method for Content Based Image Retrieval

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Advances in Neural Networks – ISNN 2018 (ISNN 2018)

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Abstract

In CBIR, images are represented by certain low-level features that describe their color, texture and shape. The combination of different image features in a global distance measurement requires normalized feature vectors. Nowaday, several normalization methods have been proposed for CBIR such as min-max, 3-sigma, and 3sigma-FCM. In this paper, we propose another method which is an upgrade from the 3sigma-FCM method. Experimentation has shown the effectiveness and efficiency of the proposed algorithm for normalizing low-level image features. The dynamic range of each component of the normalized vectors within [−1, 1] is wider than that of the 3sigma-FCM. The experiment also demonstrates that our method increases CBIR quality when combined with algorithms to define the similarity measure of images such as the EMR.

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Acknowledgments

This research is supported by the Vietnam Academy of Science and Technology under the grant VAST01.05/15-16.

Author information

Authors and Affiliations

  1. Hanoi University of Business and Technology, Hanoi, Vietnam

    Trung Xuan Hoang

  2. Belarusian State University, Minsk, Belarus

    Tuyet Van Dao & Ablameyko Sergey

  3. Vietnam National Space Center, Vietnam Academy of Science and Technology, Hanoi, Vietnam

    Tuyet Van Dao

  4. Nong Lam University Hochiminh City, Linh Trung Ward, Thu Duc District, Hochiminh City, Vietnam

    Nguyen Trinh Nguyen

  5. Electric Power University of the Vietnam Ministry of Industry and Trade, Hanoi, Vietnam

    Huy Hoang Ngo

  6. Institute of Information Technology, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet, Hanoi, Vietnam

    Huy Hoang Ngo

  7. United Institute of Informatics Problems, National Academy of Sciences of Belarus, 6, Surganova Street, 220012, Minsk, Belarus

    Ablameyko Sergey

Authors
  1. Trung Xuan Hoang
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  2. Tuyet Van Dao
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  3. Nguyen Trinh Nguyen
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  4. Huy Hoang Ngo
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  5. Ablameyko Sergey
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Corresponding author

Correspondence to Trung Xuan Hoang .

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Editors and Affiliations

  1. Texas A&M University at Qatar, Doha, Qatar

    Tingwen Huang

  2. Sichuan University, Chengdu, China

    Jiancheng Lv

  3. Southeast University, Nanjing, China

    Changyin Sun

  4. United Institute of Informatics Problems, Minsk, Belarus

    Alexander V. Tuzikov

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Hoang, T.X., Van Dao, T., Nguyen, N.T., Ngo, H.H., Sergey, A. (2018). A Novel Low Level Feature Normalization Method for Content Based Image Retrieval. In: Huang, T., Lv, J., Sun, C., Tuzikov, A. (eds) Advances in Neural Networks – ISNN 2018. ISNN 2018. Lecture Notes in Computer Science(), vol 10878. Springer, Cham. https://doi.org/10.1007/978-3-319-92537-0_71

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  • DOI: https://doi.org/10.1007/978-3-319-92537-0_71

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92536-3

  • Online ISBN: 978-3-319-92537-0

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