ICSA-ECNN based Image Forgery Detection in Face Images

Image forgery detection places a vital role in today's world. Recently, Major research work is being in process in this domain. This paper proposed a novel approach for enhanced convolution neural network-based Forgery detection techniques employed. Preprocessing is done at the initial stage to convert RGB to LAB space conversion, Proceeded with feature selection by employing image integration. The next step is to extract the features like kurtosis, Maximum Probability, Block artificial Grid. In Continuation with feature extraction, feature selection is performed using an improved crow search algorithm followed by enhanced convolution neural network classification. Finally, the performance of the proposed improved crow search algorithm is discussed.