Effect of Optimized Deep Belief Network to Patch-Based Image Inpainting Forensics

Abstract

This paper intends to propose a new model for detecting the patch based inpainting operation using Enhanced Deep Belief Network (E-DBN). The proposing model makes strong supervising of DBN that will capture the manipulated information. In fact, the enhancement is done under optimization concept, where the activation function and weight of DBN is optimally tuned by a new hybrid algorithm termed as Swarm Mutated Lion Algorithm (SM-LA). The hybridization model combines two conventional models: Group Search Optimizer (GSO) and Lion Algorithm (LA). Finally, the performance of proposed model is compared over other conventional models with respect to certain performance measures.