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基于多元分类模型的颜料红外光谱鉴别

156    2020-06-22

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作者:季佳华, 卫辰洁, 王继芬, 蒋宇航, 冯源

作者单位:中国人民公安大学侦查与刑事科学技术学院, 北京 102600


关键词:颜料;二阶导数红外光谱;判别分析;鉴别


摘要:

颜料的检验与认定是司法鉴定中一项重要的工作。在传统的分析中,侦查人员往往通过人工逐一比对和分析,其耗时长,误差大,无法满足无损、快速、准确检验现场颜料样本的需求。该文提出一种检验方法,以期实现对物证无损、快速、准确的检验与鉴定。通过采集并分析不同品牌共计48个颜料样本的红外谱图,采用多元散射校正、Savitzky-Golay平滑和峰面积归一化开展预处理工作,建立基于K近邻算法等4种分类模型,从而实现不同颜料间的区分和归类。在区分水粉类颜料和毕加索丙烯画颜料时,相较于K近邻和Fisher判别模型,多层感知器分类模型准确率更高(总体分类准确率为100%),分类结果更好。在经过主成分分析提取特征变量后,分类模型对两类颜料的区分准确率均为100%。应用MLP结合PCA构建的分类模型对颜料样本的区分效果最佳。针对水粉类中的两类即普通水粉类和毕加索水粉类颜料样本,多层感知器分类模型对其的分类准确率为97.2%,针对普通水粉类样本的两个品牌(贝碧欧和晨光),多层感知器分类模型的分类准确率为100%,实验结果理想。利用中红外光谱结合多元分类模型可实现对颜料样本准确的鉴别与区分,其快速无损准确,降低检验鉴定成本,提高检验鉴定效率,可为其他物证的鉴别与分析提供一定的参考。


Infrared spectrum identification of pigments based on multiple classification model
JI Jiahua, WEI Chenjie, WANG Jifen, JIANG Yuhang, FENG Yuan
School of Investigation and Forensic Science and Technology, People's Public Security University of China, Beijing 102600, China
Abstract: The examination and identification of pigment is an important work in judicial appraisal.In the traditional analysis, investigators often make manual comparison and analysis with the help of the infrared spectrum database, which takes a long time and has a large error, unable to meet the requirements of lossless, rapid and accurate testing of on-site pigment samples. In order to realize nondestructive, rapid and accurate testing and identification of material evidence, this experiment is to propose a testing method. The infrared spectra of 48 pigment samples from different brands were collected and analyzed. The pretreatment was carried out by using multiple scattering correction, savitzky-golay smoothing and peak area normalization, and four classification models based on k-nearest neighbor algorithm were established to realize the classification and classification of different pigments. Compared with k-nearest neighbor and Fisher's discriminant model, the classification accuracy of the multi-layer perceptrons is higher (the overall classification accuracy is 95.8%) and the classification results are better. After extracting characteristic variables through principal component analysis, the classification model can distinguish the two kinds of pigments with an accuracy rate of 100%. The classification model constructed by MLP and PCA is the best for the classification of pigment samples. For the two types of gouache, namely, ordinary gouache and Picasso gouache, the classification accuracy of the multilayer perceptrons model was 97.2%, and for the two brands of ordinary gouache samples (bebio and m&g), the classification accuracy of the multilayer perceptrons model was 100%, with satisfactory experimental results. The accurate identification and differentiation of pigment samples can be realized by using mid-infrared spectrum and multiple classification model, which is fast and non-destructive, reduces the cost of testing and identification, improves the efficiency of testing and identification, and can provide certain reference for the identification and analysis of other physical evidence.
Keywords: pigment;second derivative infrared spectrum;discriminant analysis;identification
2020, 46(6):67-71  收稿日期: 2020-01-08;收到修改稿日期: 2020-02-15
基金项目: 中国人民公安大学基本科研业务费重点项目(2019JKF223)
作者简介: 季佳华(1996-),男,江苏连云港市人,硕士研究生,专业方向为刑事科学技术
参考文献
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