Source camera identification using enhanced sensor pattern noise

Chang Tsun Li

    Research output: Contribution to journalArticlepeer-review

    289 Citations (Scopus)


    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. © 2010 IEEE.
    Original languageEnglish
    Pages (from-to)280-287
    Number of pages8
    JournalIEEE Transactions on Information Forensics and Security
    Issue number2
    Publication statusPublished - 01 Jun 2010


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