A new face authentication system for memory-constrained devices

Though biometrics to authenticate a person is a convenient tool, typical authentication algorithms by using biometrics may not be executable on the memory-constrained devices such as smart cards. We present a solution of a face authentication algorithm for the open issue. Our achievement is two-fold. One is to present a face authentication algorithm with low memory requirement, which uses support vector machines (SVM with the feature set extracted by genetic algorithms (GA). The other contribution is to suggest a method to reduce further, if needed, the amount of memory required in the authentication at the expense of verification rate by changing a controllable system parameter for a feature set size. Given a pre-defined amount of memory, this capability is quite effective to mount our algorithm on memory-constrained devices. Our experimental results show that the proposed method provides good performance in terms of accuracy and memory requirement(1).