摘要
为实现枪弹检材的快速准确匹配,提出了一种基于尺度不变特征转换(SIFT)算法的弹底窝痕配准方法及一种经验的匹配判定方法。对SIFT算法实现弹底窝痕配准进行了详细分析和分步验证,包括特征点提取、特征向量生成以及欧氏距离法初匹配,最后以随机抽样一致法(RANSAC)进行提纯,排除误匹配点对。在此基础上,总结出一种经验的痕迹匹配判定方法,即特征点密集区域法。可提取特征点密集区域,计算其面积占窝痕总面积的百分比η,以此作为匹配判定依据。基于推荐样本的实验表明:η设定为12%,已知匹配和已知不匹配的弹底窝痕可被有效区分。
In order to realize the fast and accurate matching of bullet marks,a new method based on scaleinvariant feature transform(SIFT)algorithm and an empirical trace matching method are proposed.The algorithm of SIFT is analyzed in detail and verified step by step,including feature point extraction,feature vector generation and initial matching based on European distance.Finally,the method of random sample consensus(RANSAC)is used to purify and eliminate mismatched point pairs.On the basis of this,an empirical trace matching method is summarized,namely the method of dense feature points.It can extract the dense area of feature points and calculate the percentage of the total area of the breech face,which is used as the basis for matching.The experiment based on the recommended samples,shows thatηis set to 12%,and the matched and known unmatched bullet marks can be effectively distinguished.
作者
李赵春
顾嘉梁
张浩
孙付仲
孟龙晖
陈进
LI Zhaochun;GU Jialiang;ZHANG Hao;SUN Fuzhong;MENG Longhui;CHEN Jin(College of Mechanical and Electronic Engineering,Nanjing Forestry University,Nanjing210037,China;School of Mechanical and Power Engineering,Nanjing Tech University,Nanjing211800,China;Institute of Forensic Science,Jiangsu Public Security Bureau,Nanjing210031,China)
出处
《传感器与微系统》
CSCD
2019年第9期60-63,共4页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(51205211,51305207)
关键词
枪弹痕迹识别
弹底窝痕
尺寸不变特征变换(SIFT)
随机抽样一致性
匹配方法
firearm identification
breech face impression
scale-invariant feature transform(SIFT)
random sample consensus(RANSAC)
matching method
