发光学报, 2015, 36 (11): 1335, 网络出版: 2015-11-30
利用油品紫外荧光特性的多光谱成像检测
Multispectral Imaging Detection Using The Ultraviolet Fluorescence Characteristics of Oil
紫外诱导 多光谱成像 联合熵独立分量分析 油品检测 UV excitation light multi-spectral imaging joint entropy of independent component analysis oil identification
摘要
利用石油及其产品具有的紫外荧光特性,搭建了一套紫外诱导多光谱成像系统。该系统主要由3个紫外诱导光源、8个滤波片和1个彩色CCD相机组成。采集了6种油品的多光谱图像,以有效光斑的24个颜色分量均值作为特征,提出了一种联合熵最大化的独立分量分析特征优化方法。K均值聚类和支持向量机识别结果表明,较改进前的ICA方法,该方法的特征优化性能得到了有效提高,油种识别率达到了92.3%。
Abstract
Based on the UV fluorescence phenomena of oil and its products,a multispectral imaging system was constructed. This system was composed of 3 UV excitation light sources,8 optics filters and a CCD camera. Using this system,multi-spectral images of 6 kinds of oil were collected. The mean of 24 color features of effective light spots was used as the feature set. Then,a novel method called maximize the joint entropy of independent component analysis (ICA) was proposed for K-mean cluster and SVM recognition. It is proved that this method is better than traditional ICA for feature optimized,and the identification rate is 92.3%. This result has positive significance for oil detection.
韩仲志, 万剑华, 刘杰, 刘康炜. 利用油品紫外荧光特性的多光谱成像检测[J]. 发光学报, 2015, 36(11): 1335. HAN Zhong-zhi, WAN Jian-hua, LIU Jie, LIU Kang-wei. Multispectral Imaging Detection Using The Ultraviolet Fluorescence Characteristics of Oil[J]. Chinese Journal of Luminescence, 2015, 36(11): 1335.