Age Identification System with Panoramic Image Processing Digital Molar Dental Radiograph with Adaptive Region Growing Approach Method

  • Hilman Fauzi Telkom University
  • Fajri Tsani Telkom University
  • Fahmi Oscandar Universitas Padjajaran
  • Faaiq Ammaria Adzra Telkom University

Abstract

Forensics plays a crucial role in legal enforcement, particularly in cases where objects or human victims undergoing forensic identification have suffered significant damage. Teeth offer a robust solution in the identification process due to their resilience to various circumstances. Forensic odontology focuses on dental identification for judicial purposes. One crucial parameter in forensic odontology is age estimation. Generally, an individual's dental development is directly related to age, which can be observed through the dental pulp. The dental pulp tends to narrow or widen with increasing age. In this study, an image processing system using the Adaptive Region Growing Approach (ARGA) method was developed for dental pulp molar radiograph images. Subsequently, the dental pulp images were classified using the Support Vector Machine (SVM) method. The research process encompassed data collection, image processing, feature extraction, and molar dental pulp size classification. The results demonstrated an accuracy of over 80% in the system, using specific parameters such as an adjustment threshold of OTSU 1.15, a clip limit histogram Equalization of 0.1, a polynomial kernel type, and one against one coding type for data classification into four classes. This study concludes that the Adaptive Region Growing Approach (ARGA) method and Support Vector Machine (SVM) classification can be effectively implemented in age estimation using panoramic radiograph images. This has the potential for significant applications in forensic odontology, supporting victim identification in legal enforcement.

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Published
2023-12-31
How to Cite
FAUZI, Hilman et al. Age Identification System with Panoramic Image Processing Digital Molar Dental Radiograph with Adaptive Region Growing Approach Method. JMECS (Journal of Measurements, Electronics, Communications, and Systems), [S.l.], v. 10, n. 2, p. 44-50, dec. 2023. ISSN 2477-7986. Available at: <//journals.telkomuniversity.ac.id/jmecs/article/view/6365>. Date accessed: 22 may 2024. doi: https://doi.org/10.25124/jmecs.v10i2.6365.
Section
Signal Processing