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Development of crop monitoring system using 2-channel CCD image sensor
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: Paper number 131620020, 2013 Kansas City, Missouri, July 21 - July 24, 2013. (doi: http://dx.doi.org/10.13031/aim.20131620020) @2013
Authors: Hong Sun, Hong Sun, Qain Wu, Minzan Li, Ruijiao Zhao, Lihua Zheng
Keywords: Multi-spectral image image acquisition crop monitoring chlorophyll content.
Abstract. A feasible multi-spectral acquisition system was developed for crop monitoring. The system included multi-spectral image acquisition hardware and controlling software. The multi-spectral image acquisition device was designed with a multi-spectral 2-channel CCD sensor to measure multi-spectral images in visible (red (R), green (G) and blue (B) ) and near infrared (NIR) waveband. A panel industrial control computer was applied as the system platform. The QuadMVCL2GE was used as a converter to connect the CCD sensor and controlling computer. The output of 2-CCD sensor with Camera Link was converted into Gigabit Ethernet communication protocol. The improvement of the developed system was considered to simplify the communication protocol conversion. Thus, a new simple multi-spectral image acquisition system was developed. And the controlling software interface was refined coordinately. When the system was connected, it could work following image acquisition, image display and storage, and image processing. The multi-spectral image of tomato plant canopy was collected and processed following image enhancement, canopy segmentation and vegetation index calculation. The average gray value (R, G, B and NIR) and the vegetation indices (RVI, NDVI, et al.) widely used in remote sensing were selected as the parameters for tomato chlorophyll content monitoring. The results showed that the improved multi-spectral image acquisition system could be used to evaluate the growth of tomato in the greenhouse. It provides an efficient tool to obtain crop information for precision agriculture.
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