用同调匹配轮廓分段法和 k 近邻法分析出膛子弹痕迹

IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Programming and Computer Software Pub Date : 2024-03-12 DOI:10.1134/s036176882310002x
V. A. Fedorenko, K. O. Sorokina, P. V. Giverts
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引用次数: 0

摘要

摘 要 本文讨论了如何将排弹上的土地印记图像按 "匹配 "和 "不匹配 "类别进行分类的问题。研究的目的是通过全同匹配轮廓片段(CMPS)方法提高比较弹着点图像的有效性。该方法的科学新颖之处在于通过额外的独立特征对分析进行补充,以及在痕迹比较的最后阶段使用 k 近邻算法。研究表明,采用综合方法对比较过的成对地表印象图像进行分类的准确率约为 87%。通过 CMPS 方法进行分析,可以有效比较高分辨率(每个像素约 1 μm)的土地印记图像。这项研究对自动弹道识别系统的开发人员很有意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Analysis of Traces on Discharged Bullets by the Congruent Matching Profile Segments Method and k-Nearest Neighbors

Abstract

This paper discusses the problem of classifying images of land impressions on discharged bullets in terms of the “match” and “non-match” categories. The research is aimed at improving the effectiveness of comparing land impression images by the congruent matching profile segments (CMPS) method. The scientific novelty of the approach is in supplementing the analysis with an additional independent feature, as well as in using the k-nearest neighbors algorithm at the final stage of trace comparison. The research shows that the accuracy of classification of the compared pairs of land impression images by the combined method is approximately 87%. The analysis by the CMPS method makes it possible to effectively compare land impression images with high resolution (approximately 1 μm per pixel). The research is of interest to developers of automated ballistic identification systems.

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来源期刊
Programming and Computer Software
Programming and Computer Software 工程技术-计算机:软件工程
CiteScore
1.60
自引率
28.60%
发文量
35
审稿时长
>12 weeks
期刊介绍: Programming and Computer Software is a peer reviewed journal devoted to problems in all areas of computer science: operating systems, compiler technology, software engineering, artificial intelligence, etc.
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