A compact representation of sensor fingerprint for camera identification and fingerprint matching

Ruizhe Li, Chang Tsun Li, Yu Guan

    Research output: Book chapter/Published conference paperConference paperpeer-review

    10 Citations (Scopus)
    4 Downloads (Pure)

    Abstract

    Sensor Pattern Noise (SPN) has been proved as an effective fingerprint of imaging devices to link pictures to the cameras that acquired them. In practice, forensic investigators usually extract this camera fingerprint from large image block to improve the matching accuracy because large image blocks tend to contain more SPN information. As a result, camera fingerprints usually have a very high dimensionality. However, the high dimensionality of fingerprint will incur a costly computation in the matching phase, thus hindering many interesting applications which require an efficient real-time camera matching. To solve this problem, an effective feature extraction method based on PCA and LDA is proposed in this work to compress the dimensionality of camera fingerprint. Our experimental results show that the proposed feature extraction algorithm could greatly reduce the size of fingerprint and enhance the performance in term of Receiver Operating Characteristic (ROC) curve of several existing methods.
    Original languageEnglish
    Title of host publication2015 IEEE International Conference on Acoustics, Speech, and Signal Processing: Proceedings
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages1777-1781
    Number of pages5
    Volume2015-August
    ISBN (Electronic)9781467369978
    DOIs
    Publication statusPublished - 04 Aug 2015
    Event2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Brisbane Convention & Exhibition Centre, Brisbane, Australia
    Duration: 19 Apr 201524 Apr 2015

    Conference

    Conference2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
    Country/TerritoryAustralia
    CityBrisbane
    Period19/04/1524/04/15

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