| 牛顿插值多项式-导数光谱无损检测车用保险杠 |
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| 引用本文： | 何欣龙,王继芬.牛顿插值多项式-导数光谱无损检测车用保险杠[J].激光技术,2020,44(3):333-337. |
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| 作者姓名： | 何欣龙 王继芬 |
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| 作者单位： | 中国人民公安大学刑事科学技术学院, 北京102623 |
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| 基金项目： | 中国人民公安大学2019年拔尖人才培养专项资助项目 |
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| 摘 要： | 为了提高检验鉴定效率、降低检验鉴定成本,实现对案件现场车用保险杠碎片的快速无损检测,采用了基于红外指纹光谱结合牛顿插值多项式、光谱求导和判别分析的车用保险杠鉴别方法。采集并获取奥迪等6种品牌共计40个不同型号的车用保险杠样本的红外光谱,选择牛顿多项式插值、光谱求导等方法建立了判别模型。结果表明,基于指纹区波段建立的判别模型总体准确率(80.0%)高于全波段模型(77.5%),指纹区光谱结合4次牛顿插值多项式处理后的判别准确率可到85%,经1阶导数处理后判别准确率可达100%,以判别函数DF1和DF2作为判别轴构建判别分类模型,6种品牌的样本均实现了100%的准确区分;红外指纹光谱结合4次牛顿插值多项式、1阶导数和判别分析可实现车用保险杠品牌快速、无损鉴别,且模型检测精度高。该方法具有普适性和一定的借鉴意义。
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| 关 键 词： | 光谱学 车用保险杠 判别模型 种类鉴别 |
| 收稿时间： | 2019-07-18 |
The identification about the automotive bumper based on Newton interpolation polynomial-infrared derivative spectroscopy |
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| HE Xinlong,WANG Jifen.The identification about the automotive bumper based on Newton interpolation polynomial-infrared derivative spectroscopy[J].Laser Technology,2020,44(3):333-337. |
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| Authors: | HE Xinlong WANG Jifen |
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| Affiliation: | (Institute of Forensic Science and Technology, People’s Public Security University of China, Beijing 102623, China) |
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| Abstract: | In order to improve the efficiency of identification, reduce the cost of detection, and realize the rapid and non-destructive classification of the automotive bumper fragments, a rapid and accurate identification method about the automotive bumper was proposed based on infrared fingerprint spectroscopy, Newton interpolation polynomial, spectral derivation, and discriminant analysis. Infrared spectra of six kinds of brands of bumper samples including 40 different versions were acquired in this paper, and a discriminant model was established by taking Newton polynomial interpolation, spectral derivation, and other methods into account. The results show that the overall accuracy rate of the discriminant model based on the fingerprint zone (80.0%) is higher than that of the full-band model (77.5%). The accuracy rate of the discriminant based on fingerprint spectroscopy combined with 4th Newton interpolation polynomial processing can reach 85%. Selecting DF1 and DF2 as the discriminant axis to construct the discriminant classification model, the accuracy rate of the discriminant can be promoted to 100%. In summary, combining infrared fingerprint spectroscopy, 4th Newton interpolation polynomial, first derivative and discriminant analysis, the new method has higher accuracy in detecting the automotive bumper, and provides a new idea and reference for the identification of other physical evidence in the forensic science. |
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| Keywords: | spectroscopy the automotive bumper discriminant model identification |
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