Recognizing Surgically Altered Face Images using Bat Algorithm and Comparison with Genetic Approach for Trained and Untrained Images

Abstract — Altering facial appearance using surgical procedures has raised a challenge for face recognition algorithms. Increasing popularity of plastic surgery and its effect on automatic face recognition has attracted attention from the research community. However, the nonlinear variations introduced by plastic surgery remain di cult to be modeled by existing face recognition systems. To overcome from these problems of existing system our pro-posed method uses BAT Algorithm which is a meta-heuristic optimization algorithm for premature and population diversity problem. On the plastic surgery face database, the proposed algorithm yields high identification accuracy as compared to existing algorithms and a commercial face recognition system