基于单点激光检测的枪弹弹头快速匹配系统

doi:10.3969/j.issn.1000-1093.2021.01.010

兵工学报 ›› 2021, Vol. 42 ›› Issue (1): 91-99.doi: 10.3969/j.issn.1000-1093.2021.01.010

基于单点激光检测的枪弹弹头快速匹配系统

潘楠¹，潘地林²，蒋雪梅³，刘益⁴，钱俊兵¹，赵成俊¹

(1.昆明理工大学民航与航空学院, 云南昆明 650500; 2.昆明智渊测控科技有限公司, 云南昆明 650500;3.公安部物证鉴定中心, 北京 100038; 4. 昆明信诺莱伯科技有限公司, 云南昆明 650228)

上线日期:2021-03-11
作者简介:潘楠(1986—),男,副教授，硕士生导师，博士。E-mail: 15808867407@163.com
基金资助:
国家自然科学基金地区科学基金项目（51965030）；公安部科技计划项目（2016JSYJA03）；公安部物证鉴定中心信息化建设项目（SGS2019102901）

A Bullets Fast Matching System Based on Single Point Laser Detection

PAN Nan¹， PAN Dilin²， JIANG Xuemei³， LIU Yi⁴， QIAN Junbing¹， ZHAO Chengjun¹

(1.Faculty of Civil Aviation and Aeronautics, Kunming University of Science and Technology, Kunming 650500, Yunnan, China; 2.Kunming Zhiyuan Measurement and Control Technology Co., Ltd., Kunming 650500, Yunnan, China; 3.Material Certification Center, Ministry of Public Security, Beijing 100038, China; 4.Kunming SNLAB Science-Tech Co., Ltd., Kunming 650228, Yunnan, China)

Online:2021-03-11

摘要/Abstract

摘要： 枪弹弹头膛线痕迹具有不易破坏、难以伪装、唯一性和鉴定价值高等特点，其对于枪支批量建档、确定作案枪支等均具有十分重要的意义。针对基于显微镜检测、分段照相的传统弹头膛线痕迹匹配方法存在耗时长、效率低、受主观因素影响大，无法进行量化分析的缺点，设计一种基于单点激光检测的枪弹弹头快速匹配系统。该系统对弹头进行圆心位置和圆柱轴线的自适应调整，利用激光位移传感器对枪弹弹头表面膛线痕迹沿圆周方向进行360°环绕检测，多次检测数据叠加并利用广义形态滤波将检测数据进行降噪处理后，再利用皮尔逊相关系数进行痕迹相似度匹配计算，实现弹头痕迹快速匹配。实验结果表明，弹头快速匹配系统具有检测精度高、匹配速度快、对弹头表面纹理无破坏等优点，既可用于弹头之间的一对一数据匹配，也可用于一对多数据匹配，可以有效应用于枪支批量建档和确定作案枪支的作业中。

关键词: 弹头膛线痕迹, 单点激光, 自适应调整, 广义形态滤波, 快速匹配

Abstract: The traces of bullets rifling are not easy to be destroyed, difficult to be disguised and unique, and have good identification value. The traces are of great significance to create batch firearms file and determinate the guns for crime. For the disadvantages existing in traditional microscope inspection, segmented photography and other methods, such as time-consuming, low efficiency, great influence of subjective factors on trace detection, and more difficult quantitative analysis, a fast matching system for bullets based on single-point laser detection was designed. The system adaptively adjusts the center position of bullet and the cylindrical axis, and a laser displacement sensor is then used to detect the rifling traces on the surface of bullet along the circumference. After multiple detection data are superimposed, the generalized morphological filtering is used for noise reduction of detection data, and then the matching of trace similarity is calculated using Pearson correlation coefficient, eventually achieving the fast matching of bullets. The experimental results show that the rapid matching system has the advantages of high detection accuracy, fast matching speed and no damage to the surface texture of bullets. It can be used for one-to-one data matching between bullets, and one-to-many data matching. It can be effectively applied to the batch filing of guns and the determination of guns for committing crimes.

Key words: bulletriflingtrace, single-pointlaser, adaptiveadjustment, generalizedmorphologicalfiltering, fastmatching

中图分类号:

TN247

潘楠，潘地林，蒋雪梅，刘益，钱俊兵，赵成俊. 基于单点激光检测的枪弹弹头快速匹配系统[J]. 兵工学报, 2021, 42(1): 91-99.

PAN Nan， PAN Dilin， JIANG Xuemei， LIU Yi， QIAN Junbing， ZHAO Chengjun. A Bullets Fast Matching System Based on Single Point Laser Detection[J]. Acta Armamentarii, 2021, 42(1): 91-99.

参考文献

［1］李岳松. 运用Evofinder枪弹自动识别系统对QSZ92式9 mm手枪数字化建档的研究[D]. 北京:中国人民公安大学, 2019.
LI Y S.Research on digital file establishment of QSZ92 9 mm pistol by Evofinder automatic identification system [D]. Beijing: People's Public Security University of China, 2019. (in Chinese)
[2］李岳松, 罗亚平. 运用Evofinder枪弹自动识别系统对建档手枪弹头数字化建档的研究[J]. 刑事技术, 2018, 43(5):363-368.
LI Y S, LUO Y P. Digital filing into the registered-bullet imaging database by ballistic identification system Evofinder[J]. Forensic Science and Technology, 2018, 43(5): 363-368. (in Chinese)
[3］李赵春, 周骏, 张浩, 等. 基于SURF特征的枪弹痕迹匹配方法[J]. 传感器与微系统, 2019, 38(11): 35-38.
LI Z C, ZHOU J, ZHANG H, et al. Bullet scrapping matching method based on SURF feature[J]. Transducer and Microsystem Technologies, 2019, 38(11): 35-38. (in Chinese)
[4］李轶昳, 周志飞, 张刚, 等. 利用高分子材料复制枪弹物证三维形貌及痕迹特征[J]. 刑事技术, 2019, 44(6): 497-501.
LI Y Y, ZHOU Z F, ZHANG G, et al. Ballistic evidence reproduced of its own 3D shape and marks patterns by polymer materials[J]. Forensic Science and Technology, 2019, 44(6): 497-501. (in Chinese)
[5］庄岩. 便携式X射线荧光光谱分析仪快速检测弹着痕迹的研究应用[D]. 北京:中国人民公安大学, 2019.
ZHUANG Y. Experimental study of gunshot residue spot test on impact marks by portable X-ray fluorescence spectrometry[D]. Beijing: People's Public Security University of China, 2019. (in Chinese)
[6］杨敏, 彭颖. 基于专家知识的工具痕迹系统构建研究[J]. 中国人民公安大学学报（自然科学版）, 2013, 19(2): 1-5.
YANG M, PENG Y. Study on the construction of tool trace system based on expert knowledge[J]. Journal of People's Public Security University of China (Science and Technology), 2013,19(2): 1-5. (in Chinese)
[7］杨敏, 牟丽. 弹头痕迹多尺度扩展分形检验分析[J]. 兵工学报, 2009, 30(6): 677-681.
YANG M, MOU L. Multiscale extended fractal analysis for identi- fying bullet engraving[J]. Acta Armamentarii, 2009, 30(6): 677-681. (in Chinese)
[8］杨少波. 弹头痕迹摄像与识别系统[D]. 武汉:华中科技大学,2004.
YANG S B. Imagecollection and identification system for bullet marks[D]. Wuhan: Huazhong University of Science and Techno-logy, 2004. (in Chinese)
[9］李刚, 谢子柔, 刘益, 等. 弹头膛线痕迹的单点激光检测和建档系统的设计与实现[J]. 警察技术, 2019(5):48-51.
LI G, XIE Z R, LIU Y,et al. Design and realization of single-point laser detection and archiving system for warhead rifling marks[J]. Police Technology, 2019(5): 48-51. (in Chinese)
[10］刘耀明. 基于图像处理的枪弹弹痕自动识别技术[D]. 哈尔滨:哈尔滨工业大学,2012.
LIU Y M. Automated bulletmark identification technology based on image processing[D]. Harbin: Harbin Institute of Technology, 2012. (in Chinese)
[11］ LOCK A B, MORRIS M D. Significance of angle in the statistical comparison of forensic tool marks[J]. Technometrics, 2013, 55(4): 548-561.
[12］ GAMBINO C, MCLAUGHLIN P, KUO L, et al. Forensic surface metrology: tool mark evidence[J]. Scanning, 2011, 33(5): 272-278.
[13］ BAIKER M, KEEREWEER I, PIETERMAN R, et al. Quantitative comparison of striated toolmarks[J]. Forensic Science International, 2014, 242: 186-199.
[14］ CHUMBLEY S, ZHANG S, MORRIS M D, et al. Development of a mobile toolmark characterization/comparison system[J]. Journal of Forensic Sciences, 2017, 62(1): 83-91.
[15］李一芒, 何昕, 魏仲慧. 采用三维形貌特征匹配的弹痕自动比对[J]. 哈尔滨工程大学学报, 2013, 34(3): 332-337.
LI Y M, HE X, WEI Z H. Automatic comparison of bullet marks by matching 3-D topography of different bullets[J]. Journal of Harbin Engineering University, 2013, 34(3): 332-337. (in Chinese)
[16］方海燕, 刘小勇, 乐静, 等. 球壳表面缺陷的光学复合式非接触测量[J]. 兵工学报, 2011, 32(7): 860-865.
FANG H Y, LIU X Y, LE J, et al. Optical non-contact compo- site measurement of surface defects of hemispherical shell[J]. Acta Armamentarii, 2011, 32(7): 860-865. (in Chinese)
[17］ PAN N, PAN D L, LIU Y. Study of shearing line traces laser detection system[J]. Intelligent Automation and Soft Computing, 2019, 25(2): 367-373.
[18］宫鹏涵, 周克栋, 赫雷, 等. 形态滤波方法在抵肩力信号降噪中的应用研究[J]. 兵工学报, 2017, 38(7): 1416-1421.
GONG P H, ZHOU K D, HE L, et al. Application of morphology filtering method in the de-noising of firearms' shoulder-force signals[J]. Acta Armamentarii, 2017, 38(7): 1416-1421. (in Chinese)
[19］ PAN N, KAN L F, LIU Y, et al. Nonlinear tool traces fast tracing algorithm based on single point laser detection[J]. Journal of Intelligent & Fuzzy Systems, 2019, 36(2): 1109-1120.

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基于单点激光检测的枪弹弹头快速匹配系统

A Bullets Fast Matching System Based on Single Point Laser Detection

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