Can Computer Vision Techniques be Applied to Automated Forensic Examinations? A Study on Sex Identification from Human Skulls Using Head CT Scans

Arigbabu, Olasimbo Ayodeji; Liao, Iman Yi; Abdullah, Nurliza; Noor, Noor Maizura Mohamad

doi:10.1007/978-3-319-54190-7_21

Cited by 2 publications

(1 citation statement)

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“…They obtained an accuracy of 98%, identifying the gender of a child even with half of the lower part of the hand, which is impressive considering the incompletely grown skeleton of the children. In another contribution [78], the authors examined the possibilities offered by 3D descriptors on sex identification accuracy, and tested their multi-region based representation on 100 head PM CT scans (54 male and 46 female subjects between the ages of 5 to 85 years, from south east Asia). The authors yield comparable results to the commonly reported sex prediction range (70-90%) using morphometric or morphological assessment by forensic anthropologists.…”

Section: Sex Estimation From Skeletal Structuresmentioning

confidence: 99%

A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification

et al. 2020

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This paper represents the first survey on the application of AI techniques for the analysis of biomedical images with forensic human identification purposes. Human identification is of great relevance in today’s society and, in particular, in medico-legal contexts. As consequence, all technological advances that are introduced in this field can contribute to the increasing necessity for accurate and robust tools that allow for establishing and verifying human identity. We first describe the importance and applicability of forensic anthropology in many identification scenarios. Later, we present the main trends related to the application of computer vision, machine learning and soft computing techniques to the estimation of the biological profile, the identification through comparative radiography and craniofacial superimposition, traumatism and pathology analysis, as well as facial reconstruction. The potentialities and limitations of the employed approaches are described, and we conclude with a discussion about methodological issues and future research.

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Section: Sex Estimation From Skeletal Structuresmentioning

confidence: 99%