Cross-spectral iris recognition by learning device-specific band | |
Wei Jianze1,2; Wang Yunlong2; Li Yi3; He Ran2; Sun Zhenan2 | |
发表期刊 | IEEE Transactions on Circuits and Systems for Video Technology |
2022-06 | |
卷号 | 32期号:6页码:3810 - 3824 |
摘要 | Cross-spectral recognition is still an open challenge in iris recognition. In cross-spectral iris recognition, there exist distinct device-specific bands between near-infrared (NIR) and visible (VIS) images, resulting in the distribution gap between samples from different spectra and thus severe degradation in recognition performance. To tackle this problem, we propose a new cross-spectral iris recognition method to learn spectral-invariant features by estimating device-specific bands. In the proposed method, Gabor Trident Network (GTN) first utilizes the Gabor function’s priors to perceive iris textures under different spectra, and then codes the device-specific band as the residual component to assist the generation of spectral-invariant features. By investigating the device-specific band, GTN effectively reduces the impact of device-specific bands on identity features. Besides, we make three efforts to further reduce the distribution gap. First, Spectral Adversarial Network (SAN) adopts a class-level adversarial strategy to align feature distributions. Second, Sample-Anchor (SA) loss upgrades triplet loss by pulling samples to their class center and pushing away from other class centers. Third, we develop a higher-order alignment loss to measures the distribution gap according to space bases and distribution shapes. Extensive experiments on five iris datasets demonstrate the efficacy of our proposed method for cross-spectral iris recognition. |
关键词 | iris recognition device-specific band cross- spectral recognition adversarial strategy |
学科门类 | 工学::计算机科学与技术(可授工学、理学学位) |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000805833400042 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48621 |
专题 | 智能感知与计算 |
通讯作者 | Sun Zhenan |
作者单位 | 1.School of Artificial Intelligence, University of Chinese Academy of Sciences 2.Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 3.Shool of Artificial Intelligence, Dalian University of Technology |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Wei Jianze,Wang Yunlong,Li Yi,et al. Cross-spectral iris recognition by learning device-specific band[J]. IEEE Transactions on Circuits and Systems for Video Technology,2022,32(6):3810 - 3824. |
APA | Wei Jianze,Wang Yunlong,Li Yi,He Ran,&Sun Zhenan.(2022).Cross-spectral iris recognition by learning device-specific band.IEEE Transactions on Circuits and Systems for Video Technology,32(6),3810 - 3824. |
MLA | Wei Jianze,et al."Cross-spectral iris recognition by learning device-specific band".IEEE Transactions on Circuits and Systems for Video Technology 32.6(2022):3810 - 3824. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
tcsvt_cross_wei2022.(7018KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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