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2022 | OriginalPaper | Chapter

Comparative Compression Robustness Evaluation of Digital Image Forensics

Authors : Oliver Remy, Sebastian Strumegger, Jutta Hämmerle-Uhl, Andreas Uhl

Published in: Computational Science and Its Applications – ICCSA 2022

Publisher: Springer International Publishing

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Abstract

The robustness of two important digital image forensic tasks (i.e. SIFT-based copy-move forgery detection and PRNU-based camera sensor identification) against four different lossy compression techniques is investigated (while typically, only JPEG compression is considered) to identify the best suited technique for this application scenario. Overall, we find that the accuracy of forensic tasks is reduced for increasing compression strength as expected, however, the relative performance of the compression schemes is different for the two tasks. While JPEG is superior for realistic application settings (where accuracy is in an acceptable range) in SIFT-based copy-move forgery detection, JPEG XR and BPG provide the best option for PRNU-based camera sensor identification, whereas JPEG is clearly impacting this forensic application most severely.

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Metadata
Title
Comparative Compression Robustness Evaluation of Digital Image Forensics
Authors
Oliver Remy
Sebastian Strumegger
Jutta Hämmerle-Uhl
Andreas Uhl
Copyright Year
2022
Book
Computational Science and Its Applications – ICCSA 2022

Print ISBN: 978-3-031-10449-7

Electronic ISBN: 978-3-031-10450-3

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-3-031-10450-3_19

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