基于高光谱成像结合分光光度技术的喷墨打印墨水种类鉴别方法

在法庭科学实践中，往往需要通过对文件中字迹墨水的成分分析来精确地判定检材和样本文件的同一性。利用高光谱成像和分光光度技术结合化学计量法,提出了一种对喷墨打印墨水分类的方法。采集14台不同品牌、型号的四色喷墨打印墨水高光谱数据和色度值。计算出平均色度值后进行PCA降维处理和K-Means聚类分析,将样品初步分类。之后应用LightGBM模型、XGBoost模型和SVM模型共三种分类模型,以1:4的比例确定测试集和训练集,对聚类分析结果中每一类别的样品进行逐一鉴别。结果表明,LightGBM和XGBoost对四色样品的分类精度都能达到95%以上,SVM的分类精度为100%。提出的方法能够做到无损、准确、快速地将不同品牌乃至型号的喷墨打印墨水进行区分。

Identification method of inkjet printing inks based on hyperspectral imaging combined with spectrophotometry

In the practice of forensic science, it is often necessary to accurately determine the identity of the test material and the sample document by analyzing the composition of the ink in the document.The hyperspectral imaging technology combined with machine learning was used to identify the types of inkjet printing inks. A method for classifying inkjet printing inks is presented by using hyperspectral imaging and spectrophotometry combined with chemometry.The hyperspectral data and chroma values of 14 sets of four color inkjet printing inks of different brands and models were collected.After calculating the average chromaticity value, PCA dimensionality reduction and K-Means cluster analysis were performed to classify the samples.Then three classification models, LightGBM model, XGBoost model and SVM model, were used to determine the test set and training set at a ratio of 1:4, and each class of samples in the cluster analysis results were identified one by one.The results show that the classification accuracy of both LightGBM and XGBoost can reach more than 95%, and the classification accuracy of SVM is 100%.The proposed method can distinguish different brands and models of inkjet printing inks without damage, accurately and quickly.