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A Hybrid System for Copy-Move Forgery Detection

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Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation (INFUS 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 307))

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Abstract

Copy-move forgery detection in images is an attractive topic recently dealt with by many researchers. It is still challenging to identify the location of intentionally or incidentally induced changes in the image and to determine if the image is original or not, despite a large number of both new algorithms and improved existing ones that have been proposed to this aim, achieving results with a high degree of precision. We contribute to this area of research with a proposal of a hybrid copy-move forgery detection system based on applying fuzzy S-metrics and metaheuristics to clustering. We developed the system in the programming language Python. To validate the proposed model, we compared the obtained results with those obtained by two other relevant algorithms (on the same images).

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Acknowledgements

This work has been supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia through the projects number 451-03-9/2021-14/200116 (N. M.), 451-03-9/2021-14/200116 (N. M.) and 451-03-68/2020-14/200156 (N. R., L. Č. and A. B.).

Author information

Authors and Affiliations

  1. Faculty of Agriculture, University of Belgrade, Zemun, 11080, Belgrade, Serbia

    Nataša Milosavljević

  2. Faculty of Technical Sciences, University of Novi Sad, 21000, Novi Sad, Serbia

    Nebojša Ralević, Lidija Čomić & Andrija Blesić

Authors
  1. Nataša Milosavljević
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  2. Nebojša Ralević
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  3. Lidija Čomić
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  4. Andrija Blesić
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Corresponding author

Correspondence to Nebojša Ralević .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Industrial Engineering Department, Yildiz Technical University, Istanbul, Turkey

    Selcuk Cebi

  3. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Sezi Cevik Onar

  4. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Basar Oztaysi

  5. Industrial Engineering Department, Galatasaray University, Istanbul, Turkey

    A. Cagri Tolga

  6. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Irem Ucal Sari

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Milosavljević, N., Ralević, N., Čomić, L., Blesić, A. (2022). A Hybrid System for Copy-Move Forgery Detection. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A.C., Sari, I.U. (eds) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. INFUS 2021. Lecture Notes in Networks and Systems, vol 307. Springer, Cham. https://doi.org/10.1007/978-3-030-85626-7_85

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