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用于法医应用的石英砂颗粒自动纹理识别

Automated texture recognition of quartz sand grains for forensic applications.

作者信息

Newell Andrew J, Morgan Ruth M, Griffin Lewis D, Bull Peter A, Marshall John R, Graham Giles

机构信息

Department of Computer Science, University College London, London, UK.

出版信息

J Forensic Sci. 2012 Sep;57(5):1285-9. doi: 10.1111/j.1556-4029.2012.02126.x. Epub 2012 Mar 27.

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 data sets. 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% 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%. The enhanced potential for routine forensic investigation of the provenance of common quartz sand is indicated.

摘要

石英砂表面纹理分析首次实现了自动化,用于法医应用。导出的基本图像特征(BIFs)可根据现有数据集进行计算机生成的纹理识别。该技术被应用于两个不同的分类问题;第一,系统区分具有上翻板特征的(石英)砂粒(指示风成、全球砂海环境)和不具有这些特征的砂粒的能力。砂粒分类成功率达到了98.8%。第二,测试计算机识别系统识别上翻板表面纹理特征形成的特定能量水平的能力。迄今为止,这种识别能力超出了人工地质解释的范围。判别性能提高到精确分类成功率为81%。这表明了对常见石英砂来源进行常规法医调查的潜力得到了增强。

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