Image Forensic Investigation Using Discrete Cosine Transform-Based Approach

Abstract

Digital image tempering is widespread because software and devices that manipulate image information are easily available for high-performance image editing. Now everything is online and digital images are presented as evidence of any event, documentation where forgery hides its traces. Existing techniques for forgery detection are based on the higher complexity of computational costs. The technique proposed is robust even with pre-and post-processing operations for automatic detection and localization of specific artifacts. A proposed methodology using the Discrete Cosine Transform technique was used to obtain features from each block of images that reduce the block dimension. Tampered blocks of images are compared with predefined threshold values based on robust parameters to detect similar blocks in reduced time. Experimental results show multiple forgery detection with low computational complexity and retained significance of image information. On several images that are affected by different forgery types, the proposed method acts robustly.