三维牙科生物识别:基于变压器的牙弓提取和匹配

Zhiyuan Zhang, Xin Zhong
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引用次数: 0

摘要

牙弓是一个重要的解剖特征,在评估牙齿排列和配置方面至关重要,并且在生物识别和数字法医牙科中具有人类识别的潜力。在之前的研究中,我们提出了一种自动姿态不变弓特征提取径向射线算法(RRA)和一种仅基于牙齿三维几何形状的匹配框架[1]。为了提高我们之前工作的识别精度和速度,我们在本研究中提出了一种转换器架构,该架构可以通过编码局部和全局特征来提取牙齿关键点。然后使用b样条对牙齿关键点进行鲁棒插值构建牙弓,并使用相同的识别框架进行比较。为了评估我们提出的方法的有效性,我们进行了实验,将相同的11个死后(PM)样本与200个死前(AM)样本进行匹配。结果表明,我们的方法比以前的方法具有更高的精度和更快的速度。具体来说,11个样本(100%)在200个排名列表中达到了前6.5%(13/200)的准确率,而之前的准确率为前15.5%(31/200)。此外,从200个受试者中识别单个受试者所需的时间从5分钟减少到3分钟。牙弓可以作为一个强大的过滤功能。我们的发现对现有的牙齿鉴定文献做出了重大贡献,并展示了我们的方法在生物识别、法医牙科、正畸学和人类学等不同领域的潜在实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D Dental Biometrics: Transformer-based Dental Arch Extraction and Matching
The dental arch is a significant anatomical feature that is crucial in assessing tooth arrangement and configuration and has a potential for human identification in biometrics and digital forensic dentistry. In a previous study, we proposed an auto pose-invariant arch feature extraction Radial Ray Algorithm (RRA) and a matching framework [1] based solely on 3D dental geometry. To enhance the identification accuracy and speed of our previous work, we propose in this study a transformer architecture that can extract dental keypoints by encoding both local and global features. The dental arch is then constructed through robust interpolation of the dental keypoints using B-Spline and is compared using the same identification framework. To evaluate the effectiveness of our proposed approach, we conducted experiments by matching the same 11 post-mortems (PM) samples against 200 antemortem (AM) samples. Our results show that our approach achieves higher accuracy and faster speed compared to our previous work. Specifically, 11 samples (100%) achieved a top 6.5% (13/200) accuracy out of the 200-rank list, compared to the top 15.5% (31/200) accuracy previously [1]. Additionally, the time required to identify a single subject from 200 subjects has been reduced from 5 minutes to 3 minutes. The dental arch can be used as a powerful filter feature. Our findings make a significant contribution to the existing literature on dental identification and demonstrate the potential practical applications of our approach in diverse fields such as biometrics, forensic dentistry, orthodontics, and anthropology.
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