EVALUATION OF GEOMETRIC MORPHOMETRIC APPROACH FOR ETHNICITIES DISCRIMINATION USING HANDWRITTEN NUMERAL CHARACTERS

Authors

  • Wan Nurul Syafawani Wan Mohd Taufek Forensic Science Programme, School of Health Sciences, Universiti Sains Malaysia, Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia
  • Helmi Mohd Hadi Pritam Forensic Science Programme, School of Health Sciences, Universiti Sains Malaysia, Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia
  • Wan Nur Syuhaila Mat Desa Forensic Science Programme, School of Health Sciences, Universiti Sains Malaysia, Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia
  • Dzulkiflee Ismail Forensic Science Programme, School of Health Sciences, Universiti Sains Malaysia, Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia

DOI:

https://doi.org/10.11113/jurnalteknologi.v86.21816

Keywords:

Forensic science, geometric morphometric, handwritten numeral characters, handwriting, ethnicity discrimination

Abstract

Handwriting evidence is a valuable source for authorship identification, an important aspect in investigating crimes such as murder, suicide, illegal drug trafficking, kidnapping, and document forgery. It relies heavily on the examination of written characters that make the document. However, specific studies on the handwritten numeral characters are scarce despite being crucial in assisting investigators in solving crimes. Hence, this study is aimed to gauge the possibility to discriminate authors according to their ethnicities by means of their handwritten numeral characters using a novel Geometric Morphometric (GMM) technique. Handwritten numeral characters collected from 30 individuals from three main different ethnic groups in Malaysia; Malay, Chinese and Indian were first digitised and landmarked using GMM software. Cluster patterns can be observed in the Principal Component Analysis (PCA) score plots, belonging exclusively to the three different ethnic groups. Significant differences (p<0.0001) were discovered in handwritten numerals characters 3, 4, 5, 7 and 9 amongst the three ethnicities when tested using Procrustes ANOVA, which signifying that it is possible to discriminate authors according to their ethnicities using their handwritten numeral characters. However, more sophisticated meta-analyses are needed in order to find the most effective technique for determining and discriminating the author's ethnicity.

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Published

2024-06-02

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Science and Engineering

How to Cite

EVALUATION OF GEOMETRIC MORPHOMETRIC APPROACH FOR ETHNICITIES DISCRIMINATION USING HANDWRITTEN NUMERAL CHARACTERS. (2024). Jurnal Teknologi, 86(4), 139-150. https://doi.org/10.11113/jurnalteknologi.v86.21816