Abstract:Aiming at the problem that the iris collection equipment is expensive and the image quality is poor and the iris positioning is difficult due to the iris collection based on visible light is susceptible to uneven illumination, light spots, specular reflection, eyelash occlusion, etc. A system for collecting iris images based on visible light and evaluating quality and iris positioning is designed. The system takes Raspberry Pi 3B+(RPi 3B+) as the core and drives the IMX477R image sensor to collect multiple eye images.First, the MSRCR algorithm is used to enhance the contrast of the image and the Lagrangian interpolation method is used to remove the effect of the light spot.Second, the Tenegrad function is used to evaluate the image sharpness quality.Finally,the inner edge of the iris was positioned by the gray characteristic thresholded and Daugman circular gradient algorithm, and the outer edge of the iris was positioned by the small area search method and hybrid geodesic area curve evolution method. The test results show that the iris acquisition system is stable and cost-effective, the image quality evaluation pass rate reaches 84% and the iris positioning accuracy rate reaches 91%.