An Efficient Scheme for Detecting Copy-move Forged Images by Local Binary Patterns

Leida Li, Shushang Li, Hancheng Zhu, Shu-Chuan Chu, John Roddick, Jeng-Shyang Pan

    Research output: Contribution to journalArticlepeer-review

    148 Citations (Scopus)


    Copy-move is one of the most common image tampering method. Many schemes have been proposed to detect and locate the forged regions. However, many existing schemes fail when the copied region is rotated or ipped before being pasted. To solve the problem, this paper presents a new method for detecting the copy-move forgery. The image is first filtered and divided into overlapping circular blocks. Then the features of the circular blocks are extracted using rotation invariant uniform local binary patterns (LBP). The feature vectors are then compared and the forged regions can be located by tracking the corresponding blocks. Experimental results demonstrate that this method is robust not only to JPEG compression, noise contamination and blurring, but also to region rotation and ipping.

    Original languageEnglish
    Pages (from-to)46-56
    Number of pages11
    JournalJournal of Information Hiding and Multimedia Signal Processing
    Issue number1
    Publication statusPublished - 2013


    • Copy-move forgery
    • Flipping
    • LBP
    • Rotation


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