Review on local binary patterns variants as texture descriptors for copy-move forgery detection

• Main Authors: Muhamad, R., Majid, H. A., Samah, A. A., Sulong, G., Mohamad, M. S., Kasim, S.
• Format: Article
• Language: English
• Published: Insight Society 2017
• Subjects: Q Science (General)
• Online Access: http://eprints.utm.my/id/eprint/81227/1/RafidahMuhamad2017_ReviewonLocalBinaryPatternsVariants.pdf; http://eprints.utm.my/id/eprint/81227/; http://dx.doi.org/10.18517/ijaseit.7.5.3396

Past decades had seen the concerned by researchers in authenticating the originality of an image as the result of advancement in computer technology. Many methods have been developed to detect image forgeries such as copy-move, splicing, resampling and et cetera. The most common type of image forgery is copy-move where the copied region is pasted on the same image. The existence of high similarity in colour and textures of both copied and pasted images caused the detection of the tampered region to be very difficult. Additionally, the existence of post-processing methods makes it more challenging. In this paper, Local Binary Pattern (LBP) variants as texture descriptors for copy-move forgery detection have been reviewed. These methods are discussed in terms of introduction and methodology in copy-move forgery detection. These methods are also compared in the discussion section. Finally, their strengths and weaknesses are summarised, and some future research directions were pointed out.