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个人身份识别使用横截面的手的高光谱图像

Takashi Suzuki¹

¹Osaka Metropolitan University, Center for Health Science Innovation, Smart Life Science Lab., Osaka, Japan.

Journal of biomedical optics

|December 17, 2024

概括

手掌的高光谱成像为个人识别提供了一种新的生物识别方法. 这种非侵入性技术使用人工智能来实现高精度,优于传统的血管模式方法.

科学领域:

生物识别信息生物识别信息
医疗成像医学成像
计算机视觉计算机视觉

背景情况:

超光谱成像是一种快速,非侵入性的技术,在生物识别和医学诊断中具有应用.
传统的血管模式识别方法在稳定性和简单性方面存在局限性.

研究的目的:

为了证明本地横截面高光谱手掌图像对于准确的个人识别的潜力.
建立超光谱手掌成像作为一个可行的生物识别方式.

主要方法:

利用手掌的高光谱成像与人工智能 (AI) 结合用于感兴趣区域 (ROI) 检测.
采用特征向量提取和维度减小技术,包括统一的多边近似和投影 (UMAP).
使用曲线下的面积 (AUC) 和相同错误率 (EER) 验证的个人识别准确性.

主要成果:

与主要组件分析 (PCA) 和t分布式随机邻近嵌入 (t-SNE) 相比,特征向量显示了与UMAP的增强集群内部相似性.
达到0.98的最大AUC和0.04%的相同错误率 (EER).

结论:

提出了一种新的生物识别方法,利用人手掌的横截面超光谱成像.
该方法包括基于AI的ROI检测,特征提取,维度减小和基于欧几里德距离的匹配.
该技术显示出极其精确的个人身份识别的巨大潜力.

关键词:

媒体管的手人工智能的人工智能是人工智能.生物识别信息生物识别信息超光谱成像技术的使用.个人身份证明.

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