Online personal identification in night using multiple face representations
This paper details a fully automated face authentication system using low-cost near infrared imaging. The image normalization step consists of eye center localization, scale correction and orientation correction. This paper investigates the comparison and combination of four face matchers on the automatically normalized face images: elastic bunch graph matching (EBGM), trace transform, PCA, and LDA. The performance evaluation is presented on the near infrared images acquired from the 102 users in two sessions with different pose and expressions. Our experimental results achieve the best results with the EER of 3.92% from the EBGM matcher while the combination of results from the different matchers can significantly improve the performance and achieve the EER of 2.28 %. The near infrared face database developed in this work is also made publicly available to foster further research.