A novel identification method using perceptual degree of concordance of occlusal surfaces calculated by a Python program

Miki Hori; Tadasuke Hori; Yuzo Ohno; Shozo Tsuruta; Haruhiko Iwase; Tatsushi Kawai

doi:10.1016/j.forsciint.2020.110358

A novel identification method using perceptual degree of concordance of occlusal surfaces calculated by a Python program

Forensic Sci Int. 2020 Aug:313:110358. doi: 10.1016/j.forsciint.2020.110358. Epub 2020 Jun 10.

Authors

Miki Hori¹, Tadasuke Hori², Yuzo Ohno³, Shozo Tsuruta⁴, Haruhiko Iwase⁴, Tatsushi Kawai⁵

Affiliations

¹ Department of Dental Materials Science, School of Dentistry, Aichi Gakuin University, 1-100 Kusumoto-cho, Chikusa-ku, Nagoya, Aichi 464-8650, Japan; Center for Advanced Oral Science, School of Dentistry, Aichi Gakuin University, 1-100 Kusumoto-cho, Chikusa-ku, Nagoya, Aichi 464-8650, Japan. Electronic address: mikihori@dpc.agu.ac.jp.
² Center for Advanced Oral Science, School of Dentistry, Aichi Gakuin University, 1-100 Kusumoto-cho, Chikusa-ku, Nagoya, Aichi 464-8650, Japan.
³ Department of Periodontology, School of Dentistry, Aichi Gakuin University, 2-11 Suemori-dori, Chikusa-ku, Nagoya, Aichi 464-8651, Japan.
⁴ Department of Dental Materials Science, School of Dentistry, Aichi Gakuin University, 1-100 Kusumoto-cho, Chikusa-ku, Nagoya, Aichi 464-8650, Japan.
⁵ Department of Dental Materials Science, School of Dentistry, Aichi Gakuin University, 1-100 Kusumoto-cho, Chikusa-ku, Nagoya, Aichi 464-8650, Japan; Center for Advanced Oral Science, School of Dentistry, Aichi Gakuin University, 1-100 Kusumoto-cho, Chikusa-ku, Nagoya, Aichi 464-8650, Japan.

PMID: 32563135
DOI: 10.1016/j.forsciint.2020.110358

Abstract

One of the important issues during the response to a mass disaster is the identification of victims. In this study, we verified the use of the occlusal morphology of molars for individual identification. The aim of this study was to establish a simple new method for identifying individuals from molar data. Using Python, we developed programming that included the perceptual Hash (pHash) function and the Hamming distance (HD) between antemortem data (AMD) and postmortem data (PMD). The AMD comprised 2,215 dental models. The PMD were selected from the AMD set and comprised 17 models from the same individual with changes over time. As a result, 16 PMD models (over 90%) were ranked in the top 5%. Although identification using only a single molar is difficult, there is the possibility of narrowing down victims' identity with high accuracy through verification using multiple teeth. This system is expected to be useful as a very simple method of identification.

Keywords: Concordance detection of morphological features; Disaster victim identification (DVI); Forensic dentistry; Hash function; Occlusal morphology; Programming.

MeSH terms

Dental Occlusion*
Disaster Victims
Forensic Dentistry / methods*
Humans
Image Processing, Computer-Assisted*
Imaging, Three-Dimensional
Models, Dental*
Molar / anatomy & histology*
Software*