A compressible template protection scheme for face recognition based on sparse representation

In applications using face recognition, facial images called templates should be securely managed for privacy protection and security. This paper studies a sparse representation-based face recognition system with a new template protection scheme. The proposed scheme uses two transformations for template protection; random pixel permutation and downsampling. Thanks to these transformations, protected templates can be efficiently compressed, whereas conventional schemes do not offer such functionality. Experimental results demonstrate that the system does not degrade face recognition performance even facial templates are protected. Thus, the proposed scheme can reduce the size of the template repository in practical face recognition systems.