基于虹膜纹理感知的自适应关联学习方法  

Adaptive Contextual Learning Method Based on Iris Texture Perception

作　　者：孔佳琳 张琪[1] 卫建泽 李琦[3] KONG Jialin;ZHANG Qi;WEI Jianze;LI Qi(School of Information and Cyber Security,People’s Public Security University of China,Beijing 100038,China;Institute of Microelectronics,Chinese Academy of Sciences,Beijing 100029,China;Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China)

机构地区：[1]中国人民公安大学信息网络安全学院,北京100038 [2]中国科学院微电子研究所,北京100029 [3]中国科学院自动化研究所,北京100190

出　　处：《计算机科学》2025年第4期185-193,共9页Computer Science

基　　金：国家自然科学基金(61906199,62306307);中国博士后科学基金(2024T170985)。

摘　　要：虹膜中的微结构具有较高的个体区分度,使得虹膜识别成为实现身份验证的理想选择。除了微结构本身的特征外,其间的关联性也是用于身份验证的有效判别线索。针对虹膜微结构之间的关联性,提出了一种基于虹膜纹理感知的自适应关联学习方法,该方法在关联测度模型的双分支结构基础上进行改进,融入了通道注意力和高效多尺度注意力机制来自适应地动态调整特征图,从不同细节层次的分布中捕捉特征,提高了对虹膜微结构的敏感度。为了深入挖掘来自全局和局部特征之间的关联作用,利用注意力机制对双分支网络提取到的特征进行自适应加权融合,这种加权方式可以根据输入的重要性或相关性灵活地分配不同的权重以学习最优特征关联。实验结果表明,自适应关联学习方法在虹膜识别任务中的表现出色,在多项评价指标上优于现有基线方法,具有更高的识别精度和更强的泛化能力。The microstructures in the iris exhibit a high degree of individual distinctiveness,making iris recognition an ideal choice for identity verification.In addition to the characteristics of the microstructures themselves,the context among them also serves as an effective cue for identity verification.To address the correlations between iris microstructures,an adaptive contextual learning method based on iris texture perception is proposed.This method improves upon the dual-ranch structure of contextual measures model by incorporating channel attention and efficient multi-scale attention mechanisms.These mechanisms dynamically adjust the feature maps adaptively,capturing features from different levels of detail distribution and enhancing sensitivity to iris microstructures.To thoroughly explore the correlation between global and local features,attention mechanisms are employed to adaptively fuse the features extracted by the dual-branch network.This weighting approach flexibly assigns diffe-rent weights based on the importance or relevance of the input,aiming to learn the optimal feature associations.The experimental results demonstrate that the adaptive contextual learning method performs excellently in iris recognition tasks,surpassing existing baseline methods across multiple evaluation metrics,with higher recognition accuracy and stronger generalization ability.

关 键 词：虹膜识别 生物特征识别 深度学习 注意力机制 自适应 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]