Determining the effective number and surfaces of teeth for forensic dental identification through the 3D point cloud data analysis

Arofi Kurniawan, Kouya Yodokawa, Moe Kosaka, Koichi Ito, Keiichi Sasaki, Takafumi Aoki, Toshihiko Suzuki

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


Background: The assimilation between three-dimensional (3D) imaging techniques and dental forensic science can provide rich and stable information for human identification. This study aimed to determine the effective number and surfaces of teeth for dental identification through the 3D imaging approach. Material and methods: In the present study, maxillary dental casts were fabricated from subjects who met the inclusion criteria and scanned using a 3D scanner Vivid 910. Rapidform XOS/SCAN software was used to create and trim the 3D point cloud data. Subsequently, two types of 3D surface data of dental casts were registered and the root mean square errors (RMSEs) between subjects were calculated using iterative closest point (ICP) algorithm in MATLAB. Two sets of experiments with 120 combinations of the superimposed 3D dataset were designed, termed as experiments 1 and 2. Results: In experiment 1, the difference between subjects was clearly distinguished with a minimum of six teeth of the dental arch. The results of experiment 2 suggest that the labial surfaces of the anterior teeth are sufficient to be used for dental identification. Conclusion: Through these experiments for all possible pairs of subjects, a clear difference was observed in the RMSE between the genuine and imposter pairs. These results indicate the potential of using the 3D imaging technique to achieve highly accurate human identification. It is suggested that a future study with a larger sample number will evaluate the robustness and accuracy of this method.

Original languageEnglish
Article number3
JournalEgyptian Journal of Forensic Sciences
Issue number1
Publication statusPublished - 2020 Dec 1


  • Forensic odontology
  • Forensic science
  • Personal identification
  • Root mean square error
  • Three-dimensional imaging


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