Statistical Tools for Forensic Analysis of Toolmarks

Baldwin, David ; Morris, Max ; Bajic, Stan ; Zhou, Zhigang ; Kreiser, James

Ames Laboratory

关键词: Crime Detection;    Classification;    Crime;    99 General And Miscellaneous//Mathematics, Computing, And Information Science;    Algorithms;   

DOI  :  10.2172/825030
RP-ID  :  IS-5160
RP-ID  :  W-7405-Eng-82
RP-ID  :  825030

美国|英语

来源: UNT Digital Library

【 摘 要 】

Recovery and comparison of toolmarks, footprint impressions, and fractured surfaces connected to a crime scene are of great importance in forensic science. The purpose of this project is to provide statistical tools for the validation of the proposition that particular manufacturing processes produce marks on the work-product (or tool) that are substantially different from tool to tool. The approach to validation involves the collection of digital images of toolmarks produced by various tool manufacturing methods on produced work-products and the development of statistical methods for data reduction and analysis of the images. The developed statistical methods provide a means to objectively calculate a ''degree of association'' between matches of similarly produced toolmarks. The basis for statistical method development relies on ''discriminating criteria'' that examiners use to identify features and spatial relationships in their analysis of forensic samples. The developed data reduction algorithms utilize the same rules used by examiners for classification and association of toolmarks.