红外指纹区光谱结合多阶导数融合技术无损分类鞋底物证  

Non⁃destructive Classification of Sole Based on Fingerprint Spectral Fusion Technique

作　　者：孔昊 董泽 卫辰洁 王继芬 高春芳 KONG Hao;DONG Ze;WEI Chenjie;WANG Jifen;GAO Chunfang(School of Public Security,People’s Public Security University of China,Beijing 102600,China)

机构地区：[1]中国人民公安大学治安学院,北京102600

出　　处：《中国塑料》2021年第2期94-100,共7页China Plastics

基　　金：2020年中国人民公安大学基本科研业务费重点项目(2020JKF206)。

摘　　要：为了提高检验效率,降低检验鉴定成本,实现对鞋底的快速无损分类。采用傅里叶变换红外指纹光谱及其多阶导数光谱对5类不同品牌共计50个样本的鞋底进行分析,并构建Bayes判别和支持向量机2种分类模型。结果表明,在鞋底鉴别过程中,基于原始数据、一阶导数数据和二阶导数数据建立的融合模型,初级融合模型的区分效果优于单一模型和中级融合模型,总体分类准确率能达到80%以上。而基于初级模型进行的成分特征提取中,BDA结合原始数据结合一阶导数模型是最好的,总体分类准确率达到92%。红外指纹光谱结合一阶求导、二阶求导构建不同的融合模型进行区分对比,选择最为有效的融合模型可实现对日常皮鞋、运动鞋鞋底快速的无损鉴别,对今后的治安工作作具有借鉴意义,不仅缩小排查范围,也为案件的快速侦破提供了一种新的方式。In order to improve the inspection efficiency,reduce the cost of inspection and identification,and realize the rapid and nondestructive classification of sole,a Fourier-transform infrared fingerprint spectrum and a spectral derivation were adopted to analyze the soles with five different brands among the totally 50 samples,and two classification models,Bayes discriminant(BDA)and support vector machine(SVM),were constructed.The experimental results indicated that the fusion model based on the original data,the first derivative data,and the second derivative data was superior to the single model and the intermediate fusion model in the process of sole discrimination,which resulted in an overall classification accuracy of more than 80%.Based on the primary model,the combination of BDA with the original first derivative model led to an overall classification accuracy of 92%.Different fusion models can be constructed by a combination of the infrared fingerprint spectrum with the first order derivation and the second order derivation to distinguish and contrast.The rapid non-destructive identification of daily leather shoes and sneakers soles can be realized by choosing the most effective fusion model,which provides a new way for the rapid detection of cases.

关 键 词：鞋底材料 光谱融合技术 Bayes判别分析 支持向量机分析 

分 类 号：TQ322[化学工程—合成树脂塑料工业]