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

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.