Abstract
Race determination of skulls of individuals is a continually growing subject in forensic anthropology. Traditionally, race determination has been conducted either entirely subjectively by qualified forensic anthropologists, or has been conducted through a semi-automated fashion through multivariate discriminant functions. This paper describes a novel method for completely automated race determination of CT scans of skulls, wherein skulls are preprocessed, reduced to a low dimensional model and segregated into one of two racial classes through a classifier. The classifier itself is chosen from a survey conducted against four different classification techniques. This method can both be used as a tool for completely automated race determination, or as decision support for forensic anthropologists. A total of 341 skulls with variance in race have been gathered by the University of Nottingham Malaysia Campus and used to train and test the method. The resultant accuracy of this method is 79%.
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Acknowledgments
The authors would like to thank the Hospital Kuala Lumpur for providing all data used. The research (NMRR-15-1761-2777) has received full ethics approval from the Ministry of Health, Malaysia.
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Oakley, C., Bai, L., Liao, I.Y., Arigbabu, O., Abdullah, N., Noor, M.H.M. (2019). A Novel Method for Race Determination of Human Skulls. In: Zhang, Z., Suter, D., Tian, Y., Branzan Albu, A., Sidère, N., Jair Escalante, H. (eds) Pattern Recognition and Information Forensics. ICPR 2018. Lecture Notes in Computer Science(), vol 11188. Springer, Cham. https://doi.org/10.1007/978-3-030-05792-3_9
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