Assessing the Performance of RGB-D Sensors for 3D Fruit Crop Canopy Characterization under Different Operating and Lighting Conditions
| Autor: | Eduard Gregorio, José A. Martínez-Casasnovas, Joan R. Rosell-Polo, Jaume Arnó, Francesc Solanelles, Jordi Llorens, Jordi Gené-Mola, Alexandre Escolà |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Kinect v2 agricultural robotics lcsh:Chemical technology 01 natural sciences Biochemistry Article Analytical Chemistry plant phenotyping Range (statistics) Agricultural robotics lcsh:TP1-1185 Sensitivity (control systems) Electrical and Electronic Engineering time-of-flight sensors Instrumentation Remote sensing Data processing Depth cameras depth cameras precision agriculture Precision agriculture RGB-D cameras 010401 analytical chemistry Illuminance 3D sensors RGB-D 04 agricultural and veterinary sciences 3d sensor Atomic and Molecular Physics and Optics 0104 chemical sciences 040103 agronomy & agriculture 0401 agriculture forestry and fisheries RGB color model Plant canopy Plant phenotyping |
| Zdroj: | Repositorio Abierto de la UdL Universitad de Lleida Sensors, Vol 20, Iss 7072, p 7072 (2020) Sensors Volume 20 Issue 24 Recercat. Dipósit de la Recerca de Catalunya instname Recercat: Dipósit de la Recerca de Catalunya Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) Sensors (Basel, Switzerland) |
| DOI: | 10.3390/s20247072 |
| Popis: | The use of 3D sensors combined with appropriate data processing and analysis has provided tools to optimise agricultural management through the application of precision agriculture. The recent development of low-cost RGB-Depth cameras has presented an opportunity to introduce 3D sensors into the agricultural community. However, due to the sensitivity of these sensors to highly illuminated environments, it is necessary to know under which conditions RGB-D sensors are capable of operating. This work presents a methodology to evaluate the performance of RGB-D sensors under different lighting and distance conditions, considering both geometrical and spectral (colour and NIR) features. The methodology was applied to evaluate the performance of the Microsoft Kinect v2 sensor in an apple orchard. The results show that sensor resolution and precision decreased significantly under middle to high ambient illuminance (> 2000 lx). However, this effect was minimised when measurements were conducted closer to the target. In contrast, illuminance levels below 50 lx affected the quality of colour data and may require the use of artificial lighting. The methodology was useful for characterizing sensor performance throughout the full range of ambient conditions in commercial orchards. Although Kinect v2 was originally developed for indoor conditions, it performed well under a range of outdoor conditions. |
| Databáze: | OpenAIRE |
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