Automated Texture Recognition of Quartz Sand Grains for Forensic Applications

• NCJ Number: 242055
• Journal: Journal of Forensic Sciences Volume: 57 Issue: 5 Dated: September 2012 Pages: 1285-1289
• Author(s): Andrew J. Newell, Ph.D.; Ruth M. Morgan, D.Phil.; Lewis D. Griffin, Ph.D.; Peter A. Bull, Ph.D.; John R. Marshall, Ph.D.; Giles Graham, Ph.D.
• Date Published: September 2012
• Length: 5 pages
• Publication Format: Article
• Publication Type: Report (Technical)
• Language: English
• Country: United States of America

Annotation

Quartz sand surface texture analysis has been automated for the first time for forensic application.

Abstract

Quartz sand surface texture analysis has been automated for the first time for forensic application. The derived Basic Image Features (BIFs) provide computer-generated texture recognition from preexisting datasets. The technique was applied to two distinct classification problems; first, the ability of the system to discriminate between (quartz) sand grains with upturned plate features (indicative of eolian, global sand sea environments) and grains that do not exhibit these features. A success rate of grain classification of 98.8 percent was achieved. Second, to test the ability of the computer recognition system to identify specific energy levels of formation of the upturned plate surface texture features. Such recognition ability has to date been beyond manual geological interpretation. The discrimination performance was enhanced to an exact classification success rate of 81 percent. The enhanced potential for routine forensic investigation of the provenance of common quartz sand is indicated. Abstract published by arrangement with John Wiley & Sons.