Tesla Stem High School, Redmond, Washington, United States
Research
The Rugae Classification Sequence: Using Machine Learning to Determine Gender from Characteristics of Palatal Rugae
Author(s): Amrant Singh* and Savid Gershony
Background: Palatal rugae are a series of ridges on the hard palate of the mouth with high durability and stability,
ensuring their usefulness as a tool for disaster victim identification. Additionally, certain characteristics of palatal
rugae are shared by gender or within specific age groups. Currently, forensics odontologists must manually examine
palatal rugae imprints to determine an individual’s gender, a time-consuming process vulnerable to bias and human
error.
Methodology: This project sought to automate the process of palatoscopy based classification by developing the
Rugae Classification Sequence (RCS), a comprehensive tool for gender identification based on features of the palatal
rugae. First, data important to palatal rugae–namely rugae length, width, subject age, and gender–were extracted
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DOI:
10.35248/JOY.22.6.629