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3D dental biometrics: Alignment and matching of dental casts for human identification

机译:3D牙齿生物特征识别:牙模的对准和匹配,以供人类识别

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摘要

A 3D dental biometrics framework and a pose invariant dental identification (PIDI) technique are proposed for human identification in this study. As best as we can tell, this study is the first attempt at 3D dental biometrics. Using 3D overcomes a number of key hurdles that plague 2D methods in dental identification. 60 Postmortem (PM) samples and 200 Ante mortem (AM) samples taken from multi ethnic Asian groups (Chinese, Indian and Malay) are used in this study. The PIDI technique includes algorithms for feature extraction, feature description and correspondence. The proposed feature extraction algorithm can extract the salient points from the scanned model of dental cast. The proposed feature description and the correspondence algorithm have been tested and shown to be more robust to rigid transformations compared with the related work. Preliminary experimental result achieves 94% rank-1 accuracy in a human-assisted process, while in an automated identification process, the rank-1 accuracy decreases to 80%. In addition, the developed methodology, as it is also feasible to be applied to identifying severely corrupted dental, could promptly provide a potential candidate list in mass disasters before expert investigation. The high accuracy, fast retrieval speed and the facilitated identification process suggest that the developed 3D framework is more suitable for practical use in dental biometrics applications in the future. The limitations and future work are also presented. It could be used adjunctively with the traditional 2D X-ray radiograph identification scheme to improve the efficiency of current identification process.
机译:在这项研究中,提出了3D牙齿生物识别框架和不变姿势牙齿识别(PIDI)技术。据我们所知,这项研究是3D牙齿生物识别技术的首次尝试。使用3D克服了在牙科识别中困扰2D方法的许多关键障碍。在这项研究中使用了60个来自多个亚洲种族群体(中国人,印度人和马来人)的尸检(PM)样品和200个死尸(AM)样品。 PIDI技术包括用于特征提取,特征描述和对应的算法。所提出的特征提取算法可以从牙科模型的扫描模型中提取显着点。与相关工作相比,所提出的特征描述和对应算法已经过测试,并且显示出对刚性变换更健壮。初步的实验结果在人工辅助过程中达到了94%的rank-1精度,而在自动识别过程中,rank-1的精度降低到80%。此外,已开发的方法学也可以应用于鉴定严重受损的牙齿,因此可以在专家调查之前迅速提供大规模灾难的潜在候选清单。高精度,快速检索速度和便利的识别过程表明,开发的3D框架更适合将来在牙科生物识别应用中的实际使用。还介绍了局限性和未来的工作。它可以与传统的2D X射线射线照相识别方案一起使用,以提高当前识别过程的效率。

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