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Discrete Grey Wolf Optimization for Shredded Document Reconstruction

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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018 (AISI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 845))

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Abstract

Shredded document reconstruction problem has gained more attention in the last few years. The reconstruction process is commonly involved in forensics, investigation sciences, and reconstruction of destroyed archaeological papyrus and manuscripts. Exhaustive search is common for handling such problem for small dimensions but with higher dimension, the problem becomes worse. Recently, a bio-inspired grey wolf optimizer (GWO) is a great algorithm for solving continuous problem but the nature of Shredded document reconstruction is a discrete problem, so a discrete version of GWO has been proposed and applied to it, This paper also proposed a general simple fitness function that can handle both text and image-based documents.

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Benha University, Benha, Egypt

    H. A. Badawy, Mohamed Yassien & Mahmoud Fathi

  2. Faculty of Computers and Information, Cairo University, Giza, Egypt

    E. Emary

  3. Faculty of Computer Studies, Arab Open University, Cairo, Egypt

    E. Emary

Authors
  1. H. A. Badawy
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  2. E. Emary
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  3. Mohamed Yassien
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  4. Mahmoud Fathi
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Corresponding author

Correspondence to H. A. Badawy .

Editor information

Editors and Affiliations

  1. Information Technology Department, Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Ain Shams University, Cairo, Egypt

    Mohamed F. Tolba

  3. Dubai International Academic City, The British University in Dubai, Dubai, United Arab Emirates

    Khaled Shaalan

  4. Faculty of Computers and Information, Benha University, Benha, Egypt

    Ahmad Taher Azar

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Badawy, H.A., Emary, E., Yassien, M., Fathi, M. (2019). Discrete Grey Wolf Optimization for Shredded Document Reconstruction. In: Hassanien, A., Tolba, M., Shaalan, K., Azar, A. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018. AISI 2018. Advances in Intelligent Systems and Computing, vol 845. Springer, Cham. https://doi.org/10.1007/978-3-319-99010-1_26

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