In this paper, we propose a novel algorithm for automatic camera parameter adjustment, which is exploited for getting the correct image exposure required for iris recognition. We use two-step processing, where the first step adjusts the camera parameters on the basis of a single shot, and the second step applies precise iterative adjustment. In order to get the correct iris exposure, we use a weighted mask, which is constructed offline using a set of face images. In contrast to the existing algorithms, our method does not need to be calibrated for a particular camera sensor. We show that the proposed method significantly decreases false rejection rate caused by incorrect image exposure and reduces recognition time.
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