This report presents the findings of a Federally-funded research project that sought to enhance the forensic identification of textile fibers using multivariate statistical methods.
The ability to accurately identify and characterize textile fibers is essential in crime scene investigations as it allows forensic examiners to associate fibers from a crime scene with the crime suspect(s) and/or crime victim. Collecting microspectrophotometry data from well characterized textile fibers for polymer identification and ultimate determination of how best to identify these specific fibers using multivariate statistical methods based on their unique characteristics was the primary objective of this Federally-funded research project. The data obtained from this research and the different analytical studies of the fibers examined were to be used to develop a Web-based forensic fiber database to facilitate data archiving and future identification of fibers collected in the field. The results of this project established a performance baseline that will be relevant to discussions of fiber discrimination, and improved accuracy and reliability in fiber identification, of fiber evidence collected at crime scenes.