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鞋印及其特征中随机获取特征之间的相关性。

Dependence among randomly acquired characteristics on shoeprints and their features.

作者信息

Kaplan Damary Naomi, Mandel Micha, Wiesner Sarena, Yekutieli Yoram, Shor Yaron, Spiegelman Clifford

机构信息

Department of Statistics, The Hebrew University of Jerusalem, 91905 Jerusalem, Israel.

Israel National Police Division of Identification and Forensic Science (DIFS), 1 Bar-Lev Road, 91906 Jerusalem, Israel.

出版信息

Forensic Sci Int. 2018 Feb;283:173-179. doi: 10.1016/j.forsciint.2017.11.038. Epub 2017 Dec 11.

DOI:10.1016/j.forsciint.2017.11.038
PMID:29324348
Abstract

Randomly acquired characteristics (RACs), also known as accidental marks, are random markings on a shoe sole, such as scratches or holes, that are used by forensic experts to compare a suspect's shoe with a print found at the crime scene. This article investigates the relationships among three features of a RAC: its location, shape type and orientation. If these features, as well as the RACs, are independent of each other, a simple probabilistic calculation could be used to evaluate the rarity of a RAC and hence the evidential value of the shoe and print comparison, whereas a correlation among the features would complicate the analysis. Using a data set of about 380 shoes, it is found that RACs and their features are not independent, and moreover, are not independent of the shoe sole pattern. It is argued that some of the dependencies found are caused by the elements of the sole. The results have important implications for the way forensic experts should evaluate the degree of rarity of a combination of RACs.

摘要

随机获得的特征(RACs),也称为偶然痕迹,是鞋底上的随机标记,如划痕或孔洞,法医专家利用这些标记将嫌疑人的鞋子与在犯罪现场发现的鞋印进行比对。本文研究了随机获得的特征的三个特征之间的关系:其位置、形状类型和方向。如果这些特征以及随机获得的特征彼此独立,那么可以使用简单的概率计算来评估随机获得的特征的稀有性,从而评估鞋子与鞋印比对的证据价值,而特征之间的相关性会使分析变得复杂。使用一个包含约380只鞋子的数据集,发现随机获得的特征及其特征并非相互独立,而且也不独立于鞋底图案。有人认为,发现的一些相关性是由鞋底的元素引起的。这些结果对于法医专家评估随机获得的特征组合的稀有程度的方式具有重要意义。

相似文献

1
Dependence among randomly acquired characteristics on shoeprints and their features.鞋印及其特征中随机获取特征之间的相关性。
Forensic Sci Int. 2018 Feb;283:173-179. doi: 10.1016/j.forsciint.2017.11.038. Epub 2017 Dec 11.
2
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引用本文的文献

1
Location distribution of randomly acquired characteristics on a shoe sole.鞋底随机特征的位置分布。
J Forensic Sci. 2022 Sep;67(5):1801-1809. doi: 10.1111/1556-4029.15091. Epub 2022 Jul 19.
2
Quantifying the similarity of 2D images using edge pixels: an application to the forensic comparison of footwear impressions.使用边缘像素量化二维图像的相似度:在鞋印法医比对中的应用。
J Appl Stat. 2020 Jun 11;48(10):1833-1860. doi: 10.1080/02664763.2020.1779194. eCollection 2021.
3
Interpol review of shoe and tool marks 2016-2019.
国际刑警组织2016 - 2019年鞋印和工具痕迹审查
Forensic Sci Int Synerg. 2020 Apr 2;2:521-539. doi: 10.1016/j.fsisyn.2020.01.016. eCollection 2020.
4
An algorithm to compare two-dimensional footwear outsole images using maximum cliques and speeded-up robust feature.一种使用最大团和加速稳健特征来比较二维鞋类外底图像的算法。
Stat Anal Data Min. 2020 Apr;13(2):188-199. doi: 10.1002/sam.11449. Epub 2020 Feb 21.