Robust and Optimized Algorithm for Detection of Copy-Rotate-Move Tempering

Since the entire world is covered with computerized digital data, information through digital media is not difficult to move, access, and recycle. Currently, advanced image processing tools are used to create tempered pictures. Using these apparatuses, falsifiers presented forged pictures to spread gossip and rumors. Presently, it is quite difficult for scientific divisions to demonstrate the reality of the original picture. Consequently, a new capable copy-rotate-move tempering recognition algorithm is required. To fulfill this requirement, a computationally efficient technique for copy-rotate-move tempering recognition using Zernike moments and ant colony optimization was proposed. Tests were conducted on various datasets to evaluate the effectiveness of the proposed method. The results were compared with those of the previously proposed state-of-the-art method, using metrics such as F1 score, recall, and precision. It is evident that the proposed method outperforms the currently used state-of-the-art methods.