Pre-estimation of Images for Real-time Iris Identification Systems
实时虹膜识别系统中的图像预评估检测

There are different types of bad images when an iris identification application system captures iris images.Because previous image quality evaluation methods judge an image whether bad or else by the resolution and the definition of the iris part after the iris localization,they barely can sift a few types of bad images.For improving the performance of image's real-time estimation,debasing the rate of failure to acquire and decreasing the localization errors possibility resulted from bad images,this paper proposes a new idea of the real-time pre-estimation network which pre-estimates images saved in memory before the localization or rough localization in an recognition process and decides whether it captures an iris image again or turns into the next step by the network output.The experimental result shows that the method can detects most types of bad images with fairly low false rate and little calculation and satisfies the requirement of a real-time iris recognition system.