Blind Forensics of Images using Higher Order Local Binary Pattern

Abstract

ABSTRACTExcessive dependencies on digital photographs raise the need of their forensic analysis. When some operation is performed to create fake/forged images then it disturbs the image underlying statistics. To reveal these statistics, image features need to be extracted. The Local Binary Pattern (LBP) descriptor provide good results in texture classification, face recognition, image retrieval, and facial expression recognition, and so forth. It is computationally simple and provides crucial information of image internal statistics. In this article we propose a method for image forgery detection based on higher order LBP texture descriptor. In available literature, higher order pixel analysis gives promising results in various applications that motivate us for proposing a method based on higher order analysis. Higher order analysis provides better correlation information between image pixels that is necessary in image forgery detection. This analysis provide correlation information of near and far pixels in balanced manner, that is, near pixels get more weightage in comparison to far pixels. We assess the efficacy of our proposed work on three publicly available databases and it provides better results in comparison to some of the existing techniques.