3D dental biometrics: Automatic pose-invariant dental arch extraction and matching

• Main Authors: ZHONG, Xin, ZHANG, Zhiyuan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: 3D dental biometrics; dental arch; feature extraction; human identification; Radial Ray Algorithm (RRA); Artificial Intelligence and Robotics; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/7938; https://ink.library.smu.edu.sg/context/sis_research/article/8941/viewcontent/09412829.pdf
• Institution: Singapore Management University

A novel automatic pose-invariant dental arch extraction and matching framework is developed for 3D dental identification using laser-scanned dental plasters. In our previous attempt [1-5], 3D point-based algorithms have been developed and they have shown a few advantages over existing 2D dental identifications. This study is a continuous effort in developing arch-based algorithms to extract and match dental arch feature in an automatic and pose-invariant way. As best as we know, this is the first attempt at automatic dental arch extraction and matching for 3D dental identification. A Radial Ray Algorithm (RRA) is proposed by projecting dental arch shape from 3D to 2D. This algorithm is fully automatic and fast. Preliminary identification result is obtained by matching 11 postmortem (PM) samples against 200 ante-mortem (AM) samples. 72.7% samples achieved top 5% accuracy. 90.9% samples achieved top 10% accuracy and all 11 samples (100%) achieved top 15.5% accuracy out of the 200-rank list. In addition, the time for identifying a single subject from 200 subjects has been significantly reduced from 45 minutes to 5 minutes by matching the extracted 2D dental arch. Although the extracted 2D arch feature is not as accurate and discriminative as the full 3D arch, it may serve as an important filter feature to improve the identification speed in future investigations.