Campus Units

Industrial and Manufacturing Systems Engineering, Mechanical Engineering, Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

2-2021

Journal or Book Title

Forensic Science International

Volume

319

First Page

110628

DOI

10.1016/j.forsciint.2020.110628

Abstract

Cast-off spatter patterns exhibit linear trails of elliptical stains. These characteristic patterns occur by centrifugal forces that detach drops from a swinging object covered with blood or other liquid. This manuscript describes a method to reconstruct the motion, or swing, of the object. The method is based on stain inspection and Euclidean geometry. The reconstructed swing is represented as a three-dimensional region of statistical likelihood. The reconstruction uncertainty corresponds to the volume of the reconstructed region, which is specific to the uncertainties of the case at hand. Simple numerical examples show that the reconstruction method is able to reconstruct multiple swings that are either intersecting or adjacent to each other. The robustness, spatial convergence, computing time of the reconstruction method is characterized. For the purpose of this study, about 20 cast-off experiments are produced, with motion of the swinging object documented using video and/or accelerometers. The swings follow circular or arbitrary paths, and are either human- or machine-made. The reconstruction results are compared with the experimentally documented swings. Agreement between measured and reconstructed swings is very good, typically within less than 10 cm. The method used in this study is implemented as a numerical code written in an open source language, provided in an open access repository, for purposes of transparency and access.

Comments

This is a manuscript of an article published as McCleary, Scott, Eugene Liscio, Kris De Brabanter, and Daniel Attinger. "Automated Reconstruction of Cast-off Blood Spatter Patterns based on Euclidean Geometry and Statistical Likelihood." Forensic Science International (2020): 110628. DOI: 10.1016/j.forsciint.2020.110628. Posted with permission.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Copyright Owner

Elsevier B.V.

Language

en

File Format

application/pdf

Available for download on Wednesday, December 01, 2021

Published Version

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