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

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