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Authors: Alexandre Berthet ; Chiara Galdi and Jean-Luc Dugelay

Affiliation: Department of Digital Security, Eurecom, Sophia Antipolis, France

Keyword(s): Digital Image Forensics, Camera Recognition, Verification Protocol, Deep Learning, Convolutional Neural Network, Siamese Neural Network, Dresden Image Database, SOCRatES.

Abstract: Source digital camera recognition is an important branch of digital image forensics, which aims at authenticating cameras from the captured images. By analysing the noise artifacts left on the images, it is possible to recognize the label: brand, model and device of the camera (e.g. Nikon - NikonD70 - NikonD70 of Alice). Camera recognition is increasingly difficult as the label become more precise. In the specific case of source camera recognition based on deep learning, literature has widely addressed recognition of the camera model, while the recognition of the instance of the camera (i.e. device) is currently under-studied. Moreover, we have identified a lack of protocols for performance assessment: state-of-the-art methods are usually assessed on databases that have specific compositions, such as the Dresden Image database (74 cameras of 27 models). However, using only one database for evaluation does not reflect reality, where it may be necessary to analyse different sets of dev ices that are more or less difficult to classify. Also, for some scenarios, verification (1-to-1) is better suited to camera recognition than identification (1-to-N). Based on these elements, we propose a more reliable and reproducible protocol for verification of the source camera made of three different levels (basic, intermediate and advanced) of increasing difficulty, based on camera labels (brand, model and device). State-of-the-art methods are tested with the proposed protocol on the Dresden Image Database and on SOCRatES. The obtained results prove our assumptions, with a relative drop in performance, up to 49.08% between the basic and advanced difficulty levels. Our protocol is able to assess the robustness of methods for source camera recognition, as it tests whether they are really able to correctly classify cameras in realistic contexts. (More)

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Paper citation in several formats:
Berthet, A.; Galdi, C. and Dugelay, J. (2022). Towards a More Reliable and Reproducible Protocol of Source Camera Recognition. In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-549-4; ISSN 2184-4313, SciTePress, pages 745-752. DOI: 10.5220/0010912900003122

@conference{icpram22,
author={Alexandre Berthet. and Chiara Galdi. and Jean{-}Luc Dugelay.},
title={Towards a More Reliable and Reproducible Protocol of Source Camera Recognition},
booktitle={Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2022},
pages={745-752},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010912900003122},
isbn={978-989-758-549-4},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Towards a More Reliable and Reproducible Protocol of Source Camera Recognition
SN - 978-989-758-549-4
IS - 2184-4313
AU - Berthet, A.
AU - Galdi, C.
AU - Dugelay, J.
PY - 2022
SP - 745
EP - 752
DO - 10.5220/0010912900003122
PB - SciTePress