Date of Submission

5-10-2022

Document Type

Thesis

Department

Forensic Science

Advisor

Angie Ambers, Ph.D.

Keywords

Palatal Rugae Pattern, Human Identification, Rugoscopy, Hard Palate, Rugoscopic Identity (RI)

LCSH

Identification, Palate

Abstract

Identifying humans is an integral part of the field of forensic science, as it intertwines many forensic disciplines, including anthropology, pathology, and odontology. Generally, the most widely accepted methods of human identification include DNA analysis, fingerprint analysis, and dental comparisons, which have been used by forensic scientists for over a century; however, rugoscopy, or the study of palatal rugae patterns, is emerging as a division of forensic science that has the potential to be used as a method of forensic human identification. Palatal rugae are asymmetrical ridges on the hard palate of the mouth that previous studies have suggested possess individualizing properties in humans.

In this research, patterns of palatal rugae were enhanced and classified to individualize them and create a classification system and enhancement template. Using seventy-six (76) total images of palatal rugae patterns -- sixty (60) dental casting images and sixteen (16) intraoral images -- Adobe Lightroom Classic and Photoshop were utilized to apply a series of photo enhancements to increase the detail of the palatal rugae patterns in each image. Additionally, the Santos method and Ambers/Brumit/Filipe method were used to classify and assign each image a rugoscopic identity (RI) or palatal rugae classification to assess individuality. Subsequently, the Palatal Rugae Identification System (PRIS) database was proposed to include both antemortem and postmortem images, classified by a forensic odontologist according to the Ambers/Brumit/Filipe method with the suggested photo enhancements applied. It may be concluded that palatal rugae patterns can be used for forensic human identification in place of or in tandem with existing odontological methods.

Available for download on Saturday, May 11, 2024

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