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NCJ Number: NCJ 242055     Find in a Library
Title: Automated Texture Recognition of Quartz Sand Grains for Forensic Applications
  Document URL: HTML 
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.
  Journal: Journal of Forensic Sciences  Volume:57  Issue:5  Dated:September 2012  Pages:1285 to 1289
Date Published: 09/2012
Page Count: 5
  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.
Main Term(s): Forensics/Forensic Sciences
Index Term(s): Encoding ; Electron microscopy ; Forensic geology
Type: Report (Technical)
Country: United States of America
Language: English
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