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

Abstract

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. © 2013 Elsevier B.V. All rights reserved.