Metamorph Face Maker Using Artificial Intelligence

Face morphing attack is proved to be a serious threat to the existing face recognition systems. Although a few face morphing detection methods have been put forward, the face morphing accomplices facial restoration remains a challenging problem. In this paper, a face de- morphing generative adversarial network (FD-GAN) is proposed to restore the accomplices facial image. It utilizes a symmetric dual network architecture and two levels of restoration losses to separate the identity feature of the morphing accomplice. By exploiting the captured facial image (containing the criminals identity) from the face recognition system and the morphed image stored in the e-passport system (containing both criminal and accomplices identities), the FD-GAN can effectively restore the accomplices facial image. Experimental results and analysis demonstrate the effectiveness of the proposed scheme. It has great potential to be applied for tracing the identity of face morphing attacks accomplice in criminal investigation and judicial forensics.