Source Camera Identification Using Enhanced Sensor Pattern Noise

By Chang-Tsun Li. IEEE Transactions on Information Forensics and Security, 2009

373 citations recorded by the source corpus.

Sensor pattern noises (SPNs), extracted from digital images to serve as the fingerprints of imaging devices, have been proved as an effective way for digital device identification. However, as we demonstrate in this work, the limitation of the current method of extracting SPNs is that the SPNs extracted from images can be severely contaminated by details from scenes, and as a result, the identification rate is unsatisfactory unless images of a large size are used. In this work, we propose a novel approach for attenuating the influence of details from scenes on SPNs so as to improve the device identification rate of the identifier. The hypothesis underlying our SPN enhancement method is that the stronger a signal component in an SPN is, the less trustworthy the component should be, and thus should be attenuated. This hypothesis suggests that an enhanced SPN can be obtained by assigning weighting factors inversely proportional to the magnitude of the SPN components.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/70e5076e11901ddad0207c6de8a46b635dbbd807

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Citations in the corpus

Information Forensics: An Overview of the First Decade (2013, background): “Strategic weighting techniques can be further employed during the detection to deal with different sources of inaccuracy in PRNU noise estimation [86].”
Digital image forgery detection using passive techniques: A survey (2013, methodology): “Hsiao and Pei (2005) implemented a tampering detection scheme based on blur region detection using image DCT coefficients and optional morphological operations. Sutcu et al. (2007) applied a method to detect image tampering operations that involve sharpness/blurriness adjustment based on the regular”
Digital image forensics: a booklet for beginners (2010, background): “Li [29] observed that the extraction of sensor noise from a single image might produce a pattern contaminated by the fine details and the structure”