Localization of Tampering Created with Facebook Images by Analyzing Block Factor Histogram Voting

Abstract

Facebook images get distributed within a fraction of a second, which hackers may tamper and redistribute on cyberspace. JPEG fingerprint based tampering detection techniques have major scope in tampering localization within standard JPEG images. The majority of these algorithms fails to detect tampering created using Facebook images. Facebook utilizes down-sampling followed by compression, which makes difficult to locate tampering created with these images. In this paper, the authors have proposed the tampering localization algorithm, which locates tampering created with the images downloaded from Facebook. The algorithm uses Factor Histogram of DCT coefficients at first 15 modes to find primary quantization steps. The image is divided into BXB overlapping blocks and each block is processed individually. Votes cast by these modes for conceivable tampering are collected at every pixel position and the ones above threshold are used to form different regions. High density voted region is proclaimed as tampered region.