2D Source area prediction based on physical characteristics of a regular, passive blood drip stain

Nabanita Basu, Samir Kumar Bandyopadhyay

Research output: Contribution to journalArticle

Abstract

Violent criminal acts are often accompanied by dynamic blood shedding events. Bloodstain pattern analysis particularly deals with estimation of the dynamic blood shedding events from the static bloodstain patterns that have been left at the scene. Of all the stain patterns present at a crime scene, drip stain patterns are common stain patterns one would expect to document at a violent crime scene. The paper documents statistically significant correlations between different physical parameters, such as fall height, total number of spines associated with each stain. Statistical significant correlation between the angle of impact and the total number of spines associated with each stain pattern has been established in this work. The paper propounds that the breadth of a regular drip stain is particularly significant in making predictions empirically as also statistically about the surface area from which blood has dripped leading to the formation of a particular drip stain. A data model has been developed using machine learning techniques to predict the range of surface radius from which blood has dripped and lead to the formation of a particular drip stain (Accuracy: 97.53%, Sensitivity = 0.9481, Specificity = 1).
Original languageEnglish
Pages (from-to)39-53
Number of pages14
JournalForensic Science International
Volume266
Early online date27 Apr 2016
DOIs
Publication statusPublished - Sep 2016

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