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International Workshop on Representations, Analysis and Recognition of Shape and Motion From Imaging Data

RFMI 2017: Representations, Analysis and Recognition of Shape and Motion from Imaging Data pp 181–191Cite as

A New Watermarking Method Based on Analytical Clifford Fourier Mellin Transform

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 842))

Abstract

Here, we intend to introduce a new Fourier Transform. The well-known Analytical Fourier Mellin Transform (AFMT) will be defined on Clifford Algebra in order to process colored images. The proposed Fourier Transform is called Clifford Analytical Fourier Mellin Transform (CAFMT). Its magnitude, same as AFMT modulus, is invariant against planar similarities, not only on gray level images but also on colored images. Using ACFMT magnitude, we propose a robust watermarking technique in the frequency domain.

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Authors and Affiliations

  1. CRISTAL Laboratory, GRIFT Research Group, Manouba, Tunisia

    Maroua Affes, Malek Sellami Meziou & Faouzi Ghorbel

Authors
  1. Maroua Affes
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  2. Malek Sellami Meziou
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  3. Faouzi Ghorbel
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Corresponding authors

Correspondence to Maroua Affes , Malek Sellami Meziou or Faouzi Ghorbel .

Editor information

Editors and Affiliations

  1. Ecole Centrale de Lyon/LIRIS, Lyon, France

    Liming Chen

  2. Cité Scientifique, IMT Lille Douai/CRIStAL, Villeneuve-d'Ascq Cedex, France

    Boulbaba Ben Amor

  3. Ecole Nationale des Sciences de l’Informatique de Tunisie/CRISTAL, Manouba, Tunisia

    Faouzi Ghorbel

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Affes, M., Meziou, M.S., Ghorbel, F. (2019). A New Watermarking Method Based on Analytical Clifford Fourier Mellin Transform. In: Chen, L., Ben Amor, B., Ghorbel, F. (eds) Representations, Analysis and Recognition of Shape and Motion from Imaging Data. RFMI 2017. Communications in Computer and Information Science, vol 842. Springer, Cham. https://doi.org/10.1007/978-3-030-19816-9_14

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  • DOI: https://doi.org/10.1007/978-3-030-19816-9_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19815-2

  • Online ISBN: 978-3-030-19816-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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