IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i8p1763-d1117841.html
   My bibliography  Save this article

Image Hiding in Stochastic Geometric Moiré Gratings

Author

Listed:
  • Loreta Saunoriene

    (Department of Mathematical Modelling, Kaunas University of Technology, Studentu 50-146, LT-51368 Kaunas, Lithuania)

  • Marius Saunoris

    (Department of Electronics Engineering, Kaunas University of Technology, Studentu 50-443, LT-51368 Kaunas, Lithuania)

  • Minvydas Ragulskis

    (Department of Mathematical Modelling, Kaunas University of Technology, Studentu 50-146, LT-51368 Kaunas, Lithuania)

Abstract

An image hiding scheme based on stochastic moiré gratings is proposed, discussed, and illustrated in this paper. The proposed scheme is based on a counter-intuitive optical feature of specially designed stochastic moiré gratings when similar images in the static mode become very different in the time-averaged mode. A soft computing PSO algorithm was used for the construction of stochastic gratings. Complex computational algorithms were required to construct the cover image; however, the decryption process was completely visual. The cover image must oscillate in a predefined direction and at a predefined amplitude (the amplitude of the harmonic oscillation is one of the parameters of the proposed image hiding scheme). Computational experiments were used to demonstrate the efficacy of this optical image hiding scheme based on the stochastic moiré gratings.

Suggested Citation

  • Loreta Saunoriene & Marius Saunoris & Minvydas Ragulskis, 2023. "Image Hiding in Stochastic Geometric Moiré Gratings," Mathematics, MDPI, vol. 11(8), pages 1-20, April.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:8:p:1763-:d:1117841
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/8/1763/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/8/1763/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Abbas El Dor & Maurice Clerc & Patrick Siarry, 2012. "A multi-swarm PSO using charged particles in a partitioned search space for continuous optimization," Computational Optimization and Applications, Springer, vol. 53(1), pages 271-295, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kedar Nath Das & Raghav Prasad Parouha, 2016. "Optimization with a novel hybrid algorithm and applications," OPSEARCH, Springer;Operational Research Society of India, vol. 53(3), pages 443-473, September.
    2. Das, Kedar Nath & Parouha, Raghav Prasad, 2015. "An ideal tri-population approach for unconstrained optimization and applications," Applied Mathematics and Computation, Elsevier, vol. 256(C), pages 666-701.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:8:p:1763-:d:1117841. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.