Date of Award
Spring 6-2018
Document Type
Thesis
Degree Name
Master of Science (MS)
Department/Program
Forensic Science
Language
English
First Advisor or Mentor
Nicholas D.K. Petraco
Second Reader
Peter Shenkin
Abstract
Subclass characteristics on bullets may mislead firearm examiners when they rely on traditional 2D images. In order to provide indelible examples for training and help avoid identification errors, 3D topography surface maps and statistical methods of pattern recognition are applied to toolmarks on bullets containing known subclass characteristics. This research was conducted by collecting 3D topography surface map data from land engraved areas of bullets fired through known barrels. This data was processed and used to train the statistical algorithms to predict their origin. The results from the algorithm are compared with the “right answers” (i.e. correct IDs) of the bullets in order to examine how well computational methods can work if subclass is present.
Recommended Citation
Lin, EnTni, "A 3D Characteristics Database of Land Engraved Areas with Known Subclass" (2018). CUNY Academic Works.
https://academicworks.cuny.edu/jj_etds/82
Included in
Forensic Science and Technology Commons, Multivariate Analysis Commons, Statistical Methodology Commons