Rotation Invariant Local Binary Pattern for Blind Detection of Copy-Move Forgery with Affine Transform

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10040)


For copy-move forgery, the copied region may be rotated or flipped to fit the scene better. A blind image forensics approach is proposed for copy-move forgery detection using rotation invariant uniform local binary patterns (\(LBP_{P, R}^{riu2}\)). The image is first filtered and divided into overlapped blocks with fixed size. The features are extracted from each block using \(LBP_{P, R}^{riu2}\). Then, the feature vectors are sorted and block pairs are identified by estimating the Euclidean distances of these feature vectors. Specifically, a shift-vector counter C is exploited to detect and locate tampering region. Experimental results show that the proposed approach can deal with multiple copy-move forgeries, and is robust to JPEG compression, noise, blurring region rotation and flipping.


Passive image forensics Copy-move forgery Local binary pattern (LBP) Rotation Flipping 


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.School of Information Science and EngineeringHunan UniversityChangshaChina

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