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.
Bibliographical noteFunding Information:
1 This work was supported in part by Biometrics Engineering Research Center (KOSEF). Kyunghee Lee is with the Department of Computer Science, Yonsei University, Seoul, Korea. Also, She is currently working for Biometrics Technology Research Team, ETRI, Daejeon, Korea (e-mail: email@example.com). Hyeran Byun is with the Department of Computer Science, Yonsei University, Seoul , Korea (e-mail: firstname.lastname@example.org). Contributed Paper Manuscript received June 12, 2003 0098 3063/00 $10.00 © 2003 IEEE
All Science Journal Classification (ASJC) codes
- Media Technology
- Electrical and Electronic Engineering