A High Throughput Integrated Hyperspectral Imaging and 3D Measurement System

被引:14
作者
Zhao, Huijie [1 ]
Xu, Lunbao [1 ]
Shi, Shaoguang [1 ]
Jiang, Hongzhi [1 ]
Chen, Da [1 ]
机构
[1] Beihang Univ, Sch Instrumentat Sci & Optoelect Engn, Beijing 100191, Peoples R China
基金
美国国家科学基金会;
关键词
hyperspectral measurement; 3D structure measurement; grating dispersion; stereo vison; agriculture; PLANT-GROWTH; CAMERA CALIBRATION; PARAMETERS; RECONSTRUCTION; SPECTROSCOPY; INFORMATION; PHENOMICS; PIPELINE; PLATFORM; FUSION;
D O I
10.3390/s18041068
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Hyperspectral and three-dimensional measurements can obtain the intrinsic physicochemical properties and external geometrical characteristics of objects, respectively. The combination of these two kinds of data can provide new insights into objects, which has gained attention in the fields of agricultural management, plant phenotyping, cultural heritage conservation, and food production. Currently, a variety of sensors are integrated into a system to collect spectral and morphological information in agriculture. However, previous experiments were usually performed with several commercial devices on a single platform. Inadequate registration and synchronization among instruments often resulted in mismatch between spectral and 3D information of the same target. In addition, using slit-based spectrometers and point-based 3D sensors extends the working hours in farms due to the narrow field of view (FOV). Therefore, we propose a high throughput prototype that combines stereo vision and grating dispersion to simultaneously acquire hyperspectral and 3D information. Furthermore, fiber-reformatting imaging spectrometry (FRIS) is adopted to acquire the hyperspectral images. Test experiments are conducted for the verification of the system accuracy, and vegetation measurements are carried out to demonstrate its feasibility. The proposed system is an improvement in multiple data acquisition and has the potential to improve plant phenotyping.
引用
收藏
页数:17
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