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A Method to Detect Repeated Unknown Patterns in an Image

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Image Analysis and Recognition (ICIAR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8814))

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Abstract

Consider a natural image that has been manipulated by copying, transforming and pasting back fragments of the image itself. Our goal is to detect such manipulations in the absence of any knowledge about the content of the repeated fragments or the transformations to which they might have been subject. The problem is non-trivial even in the absence of any transformations. For example, copy/paste of a textured fragment of a background can be difficult to detect even by visual inspection. Our approach to the problem is a two-step procedure. The first step consists in extracting features from the image. The second step explores the connection between image compression and complexity: a finite-context model is used to build a complexity map of the image features. Patterns that reappear, even in a somewhat modified form, are encoded with fewer bits, a fact that renders the detection of the repeated regions possible.

Funded in part by National Funds through FCT - Foundation for Science and Technology, in the context of the project PEst-OE/EEI/UI0127/2014.

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Author information

Authors and Affiliations

  1. IEETA/DETI, Universidade de Aveiro, Aveiro, Portugal

    Paulo J. S. G. Ferreira & Armando J. Pinho

Authors
  1. Paulo J. S. G. Ferreira
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  2. Armando J. Pinho
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Corresponding author

Correspondence to Armando J. Pinho .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Porto, Porto, Portugal

    Aurélio Campilho

  2. Dept. of Electrical and Computer Eng., University of Waterloo, Waterloo, Ontario, Canada

    Mohamed Kamel

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Ferreira, P.J.S.G., Pinho, A.J. (2014). A Method to Detect Repeated Unknown Patterns in an Image. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8814. Springer, Cham. https://doi.org/10.1007/978-3-319-11758-4_2

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  • DOI: https://doi.org/10.1007/978-3-319-11758-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11757-7

  • Online ISBN: 978-3-319-11758-4

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