Noiseprint: A CNN-Based Camera Model Fingerprint

University of Naples Federico II

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Abstract

Forensic analyses of digital images rely heavily on the traces of in-camera and out-camera processes left on the acquired images. Such traces represent a sort of camera fingerprint. If one is able to recover them, by suppressing the high-level scene content and other disturbances, a number of forensic tasks can be easily accomplished. A notable example is the PRNU pattern, which can be regarded as a device fingerprint, and has received great attention in multimedia forensics. In this paper, we propose a method to extract a camera model fingerprint, called noiseprint, where the scene content is largely suppressed and model-related artifacts are enhanced. This is obtained by means of a Siamese network, which is…

Citation impact

453
total citations
FWCI
19.60
Percentile
100%
References
85
Citations per year

Authors

2

Topics & keywords

Keywords
  • Computer science
  • Fingerprint (computing)
  • Artificial intelligence
  • Computer vision
  • Digital camera
  • Fingerprint recognition
  • Focus (optics)
  • Digital forensics
UN Sustainable Development Goals
  • Peace, Justice and strong institutions
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