计算机科学与探索2024，Vol.18Issue(6)：1421-1437,17.DOI:10.3778/j.issn.1673-9418.2312062
基于深度学习的虹膜识别研究综述
Review of Deep Learning Based Iris Recognition
摘要
Abstract
The highly accurate,secure,and stable biometric technology of iris recognition is well-known.The cur-rent iris recognition system shows stable performance under the condition of constraints on user status and acquisi-tion equipment,but it cannot adapt to the current complex and diverse open scenes.Open scenarios contain a large number of uncertain acquisition factors,for example,iris images acquired in open scenarios are easily interfered by factors such as eyelashes,hair blockage,and specular reflection,etc.These uncertainties often lead to an overall decline in image quality,resulting in a significant decline in the performance of iris image segmentation and feature extraction.In recent years,deep learning algorithms have been widely used in iris recognition,aiming to improve the adaptability of the system to open scenarios.The current status of the application of deep learning technology in iris recognition is reviewed,and its key role in improving recognition accuracy in open scenarios is summarized.Firstly,the background of iris recognition is presented.Secondly,the performance of various deep learning models in iris segmentation,iris feature extraction and feature matching tasks is analyzed,and their advantages and limitations are expounded.Then,the common iris datasets and their characteristics are systematically summarized.Lastly,new challenges and potential directions for future exploration of iris recognition are pointed out.关键词
虹膜识别/生物特征识别/模式识别/计算机视觉/深度学习Key words
iris recognition/biometrics/pattern recognition/computer vision/deep learning分类
信息技术与安全科学引用本文复制引用
江健,张琪,王财勇..基于深度学习的虹膜识别研究综述[J].计算机科学与探索,2024,18(6):1421-1437,17.基金项目
国家自然科学基金(61906199,62106015) （61906199,62106015）
中国人民公安大学研究生课程建设项目(2022yjskcjs038).This work was supported by the National Natural Science Foundation of China(61906199,62106015),and the Graduate Course Con-struction Project of People's Public Security University of China(2022yjskcjs038). （2022yjskcjs038）
