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一种用于后膛面压痕图像相关性的归一化全等匹配区域方法。

A Normalized Congruent Matching Area Method for the Correlation of Breech Face Impression Images.

作者信息

Chen Zhe, Song John, Chu Wei, Tong Mingsi, Zhao XueZeng

机构信息

School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China.

National Institute of Standards and Technology, Gaithersburg, MD 20899 USA.

出版信息

J Res Natl Inst Stand Technol. 2018 Aug 6;123:1-14. doi: 10.6028/jres.123.015. eCollection 2018.

Abstract

The congruent matching cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for firearm evidence identification and error rate estimation. The CMC method divides the correlated image pairs into cells and uses four parameters to quantify topography similarity and pattern congruency of the correlated cell pairs in firearm breech face impressions on fired cartridge cases. A preliminary conservative numerical identification criterion of = 6 CMCs was suggested for identifying images of cartridge cases fired from the same firearm. The CMC method was validated by correlations using both three-dimensional (3D) topography images and two-dimensional (2D) optical images from a set of 40 cartridge cases fired from a firearm set composed of 10 consecutively manufactured pistol slides. However, in the original CMC method, due to the difference in the effective data area of the correlated cells, final CMCs obtained from an image pair presented different data quantity (or validity level), and thus the empirical criterion = 6 CMCs did not remain optimal for identification when the correlated cell size changed. In this study, a normalized congruent matching area (NCMA) method that considers the difference in the data area in each correlated cell pair was developed. Based on the NCMA method, an optimal range of cell sizes for breech face identification with granular characteristics was determined. A binomial model was used to fit the known nonmatching NCMA probability distribution , and a beta-binomial model was used to fit the known matching NCMA probability distribution . An experimental improvement in the normalized identification criterion of around 6 % was observed in the validation tests when the cell sizes were in the optimal range.

摘要

全等匹配单元(CMC)方法是美国国家标准与技术研究院(NIST)发明的用于枪支证据识别和错误率估计的方法。CMC方法将相关图像对划分为单元,并使用四个参数来量化已发射弹壳上枪支后膛面压痕中相关单元对的地形相似性和图案一致性。对于识别从同一支枪支发射的弹壳图像,建议了一个初步的保守数值识别标准,即 = 6个CMC。使用由10个连续制造的手枪滑膛组成的一组枪支发射的40个弹壳的三维(3D)地形图像和二维(2D)光学图像进行相关性分析,对CMC方法进行了验证。然而,在原始的CMC方法中,由于相关单元的有效数据区域存在差异,从图像对中获得的最终CMC呈现出不同的数据量(或有效性水平),因此当相关单元大小改变时,经验标准 = 6个CMC对于识别并不总是最优的。在本研究中,开发了一种考虑每个相关单元对数据区域差异的归一化全等匹配面积(NCMA)方法。基于NCMA方法,确定了具有颗粒特征的后膛面识别的最佳单元大小范围。使用二项式模型拟合已知的不匹配NCMA概率分布 ,并使用贝塔 - 二项式模型拟合已知的匹配NCMA概率分布 。当单元大小处于最佳范围时,在验证测试中观察到归一化识别标准 有大约6%的实验性改进。

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