Non-intrusive Forensic Detection Method Using DSWT with Reduced Feature Set for Copy-Move Image Tampering

Abstract

The key intention of non-intrusive image forensic detection is to resolve whether an image is original or tampered. In contrast to intrusive methods, there is no supporting pattern that has been embedded into an image to ensure image authenticity. The only accessible cue is the original characteristics of an image. Various non-intrusive techniques have been proposed to ensure image authenticity but no adequate solution exists so far. This article introduced a robust technique by means of Discrete Stationary Wavelet Transform along with Multi Dimension Scaling to detect familiar category of copy-move image tampering. Experimental outcomes shows that proposed technique decreases computational complexity by reducing feature dimension and locate the tampered region more accurately even when the tampered image is blurred, brightness altered, colour reduced and pasted in multiple locations. Overall tamper detection accuracy is greater than 97% and false positive rate close to zero, which indicates that proposed technique will discover tampered region more precisely compared with existing methods.