Abstract: Aiming at the evaluation index of iris quality was single or too many, we proposed a sequential iris quality evaluation algorithm based on GA-BP neural network. Firstly, the rough quality of iris image was evaluated, and most of the unqualified images with poor quality were screened out. Secondly, we evaluated the fine quality of iris image and selected three important indexes to obtain the index value. Finally, the final evaluation of image quality was carried out by combining BP neural network with precise quality evaluation index. It was verified in JLU-6.0 iris library, and compared with other algorithms, the results show that the algorithm can retain more effective iris images and has higher classification accuracy.

Key words: iris quality evaluation, sequential iris, BP neural network, accuracy