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Citation: He Xinlong, Wang Jifen, Zhang Qian, Tang Minli, He Ya. Infrared Spectroscopy Analysis of Marker Ink based on Multi-classification Model[J]. Chemistry, ;2019, 82(2): 169-174. shu

Infrared Spectroscopy Analysis of Marker Ink based on Multi-classification Model

He Xinlong ¹ ,
Wang Jifen ^1,, ,
Zhang Qian ¹ ,
Tang Minli ² ,
He Ya ¹

1.
Institute of Forensic Science and Technology, Chinese National Police University, Beijing 102600
2.
East Branch of Public Security Bureau, Panzhihua 617000

Corresponding author: Wang Jifen, wangjifen58@126.com
Received Date: 25 July 2018
Accepted Date: 30 October 2018

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It's especially important for identifying the marker pens ink in the detection and litigation of related cases. This paper acquired the original spectra of the marker pens ink by ATR-FTIR, and used automatic baseline correction, Savitzky-Golay smoothing, peak area normalization and wavelet threshold denoising to eliminate interference factors, determine the characteristic wavelength range and pretreat the original spectrum. Simultaneously, the paper combined with discriminant analysis (DA), radial basis function neural network (RBF) and K nearest neighbor algorithm (KNN) to construct multi-classification model. The results showed that the three models have the most accurate classification of black pens and achieve 100% recognition, followed by the the red and blue pens. Compared with DA and RBF, KNN model has the highest classification accuracy. Using ATR-FTIR combined with DA-RBF-KNN can provide a new analysis method for more accurate detection of marker pens ink. The method has certain universality and reference significance.
- IR,
- Marker pens ink,
- Discriminant analysis,
- Radial basis function neural network,
- K-nearest neighbor
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