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High production output stands against impact on the environment through intense use of fertilizer and pesticides. Manual work comes along with high cost for employees. Automation contributes to finding a reasonable compromise. Machine vision applied under outdoor conditions in daily changing surroundings is the key to successful operation. System with extended spectral ranges – typically named hyper spectral imaging systems – have contributed to progress in recent time. Unfortunately, the system cost has to be considered to shift from scientific research to field application. Here new approaches using Artificial Intelligence (AI) can enable reliable operation for reasonable effort. In the example presented here, imaging takes place by means of standard camera equipment. The image content is evaluated applying AI algorithms. In the next step the spectrally resolved measurements are performed on selected spots by means of robot control or additional MEMS based deflection systems. In turn fast accurate and reliable results are achieved to initiate the relevant action most efficient and maximize the user benefit.
Heinrich Grüger,Jens Knobbe, andTino Pügner
"Multi- and hyperspectral imaging of plants and their properties by means of highly integrated and MEMS based systems", Proc. SPIE 12879, Photonic Technologies in Plant and Agricultural Science, 1287903 (12 March 2024); https://doi.org/10.1117/12.3002114
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Heinrich Grüger, Jens Knobbe, Tino Pügner, "Multi- and hyperspectral imaging of plants and their properties by means of highly integrated and MEMS based systems," Proc. SPIE 12879, Photonic Technologies in Plant and Agricultural Science, 1287903 (12 March 2024); https://doi.org/10.1117/12.3002114