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A Robust Approach for Crop Misalignment Estimation in Single and Double JPEG Compressed Images

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Image Analysis and Processing - ICIAP 2023 Workshops (ICIAP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14365))

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Abstract

In forensics investigation, information about the crop performed after a JPEG compression can be useful exploited to reconstruct the manipulation history of the analyzed images and localize forgeries. Statistics computed from AC histograms, obtained performing an additional JPEG compression with a set of constant quantization matrices, are exploited to design a robust and effective algorithm to retrieve information about the employed crop. Finally, the effectiveness of the proposed solution has been demonstrated through a series of tests conducted considering different patch sizes, quantization matrices, and comparisons with a state-of-the-art solution in single and double JPEG compression scenario.

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Acknowledgements

Acknowledge financial support from: PNRR MUR project PE0000013-FAIR.

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Authors and Affiliations

  1. University of Cagliari, Cagliari, Italy

    Giovanni Puglisi

  2. University of Catania, Catania, Italy

    Sebastiano Battiato

Authors
  1. Giovanni Puglisi
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  2. Sebastiano Battiato
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Correspondence to Giovanni Puglisi .

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Editors and Affiliations

  1. University of Udine, Udine, Italy

    Gian Luca Foresti

  2. University of Udine, Udine, Italy

    Andrea Fusiello

  3. University of York, York, UK

    Edwin Hancock

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Puglisi, G., Battiato, S. (2024). A Robust Approach for Crop Misalignment Estimation in Single and Double JPEG Compressed Images. In: Foresti, G.L., Fusiello, A., Hancock, E. (eds) Image Analysis and Processing - ICIAP 2023 Workshops. ICIAP 2023. Lecture Notes in Computer Science, vol 14365. Springer, Cham. https://doi.org/10.1007/978-3-031-51023-6_27

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  • DOI: https://doi.org/10.1007/978-3-031-51023-6_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-51022-9

  • Online ISBN: 978-3-031-51023-6

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