Forensic detection of Median filtering in Images using Local Tetra Patterns and J-Divergence

Abstract

This paper presents a novel application of local tetra patterns to the median filtering detection problem. The premise of the proposed method is based on the ability of the local tetra patterns in identifying the streaking fingerprints left over by the application of a median filter on an image. These streaking fingerprints serve as a clue in determining the authenticity of an image towards the application of a median filter. The streaking pixels are identified by establishing the relationship of every pixel with respect to its neighboring pixels. The relationship is in the form of horizontal and vertical derivative directions and magnitudes followed by the tetra pattern and magnitude assignment. The feature vector generated utilizing the local tetra patterns is reduced by using the J-divergence in-order to keep the computational complexity low. Experimental testing for the proposed method along with comparative analysis carried out with existing state-of-the-art methods shows good performance at reduced computational complexity for the proposed method.