摘要
针对虹膜质量评价指标单一或过多的情形,提出一种基于GA-BP神经网络的序列虹膜质量评价算法.首先对虹膜图像进行粗质量评价,筛选掉大多数不合格的较差质量图像;然后对虹膜图像进行精质量评价,选用3个较重要的指标得出指标值;最后结合BP神经网络融合精质量评价指标进行图像质量的最终评价.在JLU-6.0虹膜库中进行验证,并与其他算法进行对比测试,测试结果表明,该算法能保留较多的有效虹膜图像,且分类精确度较高.
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.
作者
张齐贤
朱晓冬
刘元宁
王超群
吴祖慷
李昕龙
ZHANG Qixian;ZHU Xiaodong;LIU Yuanning;WANG Chaoqun;WU Zukang;LI Xinlong(Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,Jilin University,Changchun 130012,China;College of Software,Jilin University,Changchun 130012,China;College of Computer Science and Technology,Jilin University,Changchun 130012,China)
出处
《吉林大学学报（理学版）》
CAS
北大核心
2020年第6期1382-1390,共9页
Journal of Jilin University:Science Edition
基金
国家自然科学基金(批准号:61471181)
吉林省产业创新专项基金(批准号:2019C053-2)。
