Shaikh Muhammad Saad, Jaferzadeh Keyvan, Thörnberg Benny, Casselgren Johan
Department of Electronics Design, Mid Sweden University, 851 70 Sundsvall, Sweden.
Department of Computer Science and Software Engineering, Concordia University, Montreal, QC H3G 1M8, Canada.
Sensors (Basel). 2021 May 27;21(11):3738. doi: 10.3390/s21113738.
In this paper, we present a hyper-spectral imaging system and practical calibration procedure using a low-cost calibration reference made of polytetrafluoroethylene. The imaging system includes a hyperspectral camera and an active source of illumination with a variable spectral distribution of intensity. The calibration reference is used to measure the relative reflectance of any material surface independent of the spectral distribution of light and camera sensitivity. Winter road conditions are taken as a test application, and several spectral images of snow, icy asphalt, dry asphalt, and wet asphalt were made at different exposure times using different illumination spectra. Graphs showing measured relative reflectance for different road conditions support the conclusion that measurements are independent of illumination. Principal component analysis of the acquired spectral data for road conditions shows well separated data clusters, demonstrating the system's suitability for material classification.
在本文中,我们展示了一种利用由聚四氟乙烯制成的低成本校准参考物的高光谱成像系统及实用校准程序。该成像系统包括一台高光谱相机和一个具有可变强度光谱分布的有源照明源。该校准参考物用于测量任何材料表面的相对反射率,而与光的光谱分布和相机灵敏度无关。以冬季道路状况作为测试应用,使用不同的照明光谱在不同曝光时间拍摄了雪、结冰沥青、干燥沥青和潮湿沥青的几张光谱图像。显示不同道路状况下测量所得相对反射率的图表支持了测量与照明无关这一结论。对获取的道路状况光谱数据进行主成分分析显示出数据聚类分离良好,证明了该系统适用于材料分类。