ArticleSensors (Basel, Switzerland)2018
A High Throughput Integrated Hyperspectral Imaging and 3D Measurement System.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Design of a binocular multispectral stereo imaging system and its application in plant phenotyping.Plant phenomics (Washington, D.C.) · 2025Article
- Rotational hyperspectral scanner and related image reconstruction algorithm.Scientific reports · 2021Article
- Depth Density Achieves a Better Result for Semantic Segmentation with the Kinect System.Sensors (Basel, Switzerland) · 2020Article
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Authors and funding
5 authors.
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Abstract
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.
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Registered trials
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