Multibiometric systems have been recently developed in order to overcome some weaknesses of single biometric authentication systems, but security of these systems against spoofing has not received enough attention. In this paper, we propose a novel practical method for simulation of possibilities of spoof attacks against a biometric authentication system. Using this method, we model matching scores from standard to completely spoofed genuine samples. Sum, product, and Bayes fusion rules are applied for score level combination. The security of multimodal authentication systems are examined and compared with the single systems against various spoof possibilities. However, vulnerability of fused systems is considerably increased against spoofing, but their robustness is generally higher than single matcher systems. In this paper we show that robustness of a combined system is not always higher than a single system against spoof attack. We propose empirical methods for upgrading the security of multibiometric systems, which contain how to organize and select biometric traits and matchers against various possibilities of spoof attack. These methods provide considerable robustness and present an appropriate reason for using combined systems against spoof attacks.
Quality testing of optics which is used in laboratories is one of the most important tasks and many procedures are proposed and used. These testing procedures are based on measurement of reflecting laser wavefront from optical component surfaces. By using the Shack-Hartmann method, we can measure a simple curved laser beam wavefront. For achieving this, firstly we reduce optical noise which may disturb our optical data. We improved peak location and sum location algorithms to introduce a simple new algorithm, based on adaptive thresholding. The proposed algorithm scans the image to identify the approximate location of focal spots by looking for local optical centers on CCD screen.