An improved fingerprinting algorithm for detection of video frame duplication forgery

Yongjian Hu, Yufei Wang, Chang Tsun Li, Bei Bei Liu

    Research output: Book chapter/Published conference paperChapter (peer-reviewed)peer-review

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    Frame duplication is a common way of digital video forgeries. State-of-the-art approaches of duplication detection usually suffer from heavy computational load. In this paper, the authors propose a new algorithm to detect duplicated frames based on video sub-sequence fingerprints. The fingerprints employed are extracted from the DCT coefficients of the temporally informative representative images (TIRIs) of the sub-sequences. Compared with other similar algorithms, this study focuses on improving fingerprints representing video sub-sequences and introducing a simple metric for the matching of video sub-sequences. Experimental results show that the proposed algorithm overall outperforms three related duplication forgery detection algorithms in terms of computational efficiency, detection accuracy and robustness against common video operations like compression and brightness change.
    Original languageEnglish
    Title of host publicationEmerging digital forensics applications for crime detection, prevention, and security
    EditorsChang-Tsun Li
    Place of PublicationHershey, PA
    PublisherInformation Science Reference
    Number of pages13
    ISBN (Electronic)9781466640078
    ISBN (Print)9781466640061
    Publication statusPublished - 31 May 2013


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