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Classification of pistol via numerical based features of firing pin impression image

机译:通过基于撞针印象图像的基于数字的特征对手枪进行分类

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A lot of current crime cases have been reported to involve pistols, among other firearms. The whole firing pin impression image on a cartridge case is one of the most substantial clues for firearms identification. In this study, a total of 16 features of geometric moments up to the sixth order were extracted from the entire firing pin impression images. All five pistols of the Parabellum Vector SPI 9mm model, manufactured in South Africa were used. The pistols were marked Pistol A, Pistol B, Pistol C, Pistol D, and Pistol E. A total of 747 bullets have been launched from the five pistols. Under an initial analysis, Pearson correlation coefficients between all pairs of features have demonstrated that the features were significant and that the features were inter-related. These problematic featureswere solved by dividing the features into subgroups of variables based on the same characteristics under the principle component analysis. The features that are highly correlated were brought together into meaningful components or factors. Discriminant analysis was applied for the identification of the types of pistols used based on the factors obtained. Classification results using cross-validation under the discriminant analysis pointed that 65.7% of the images were rightly classified according to the pistols used.
机译:据报道,目前许多犯罪案件都涉及手枪和其他枪支。弹壳上的整个撞针印象图像是枪支识别最重要的线索之一。在这项研究中,从整个撞针压印图像中提取了总共16个直至第六阶的几何矩特征。使用了南非制造的Parabellum Vector SPI 9mm型号的所有五支手枪。这些手枪被标记为手枪A,手枪B,手枪C,手枪D和手枪E。从这五把手枪中总共发射了747枚子弹。根据初步分析,所有特征对之间的Pearson相关系数已证明这些特征很重要,并且这些特征是相互关联的。通过在主成分分析下基于相同特征将特征划分为变量子组,可以解决这些问题特征。高度相关的功能被整合到有意义的组件或因素中。基于获得的因素,判别分析用于鉴定所用手枪的类型。在判别分析下使用交叉验证进行分类的结果表明,根据所使用的手枪,正确分类了65.7%的图像。

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