An FPGA-based smart camera for accurate chlorophyll estimations
| Autor: | J.L. Camas-Anzueto, Rubén Grajales-Coutiño, Abiel Aguilar-González, M. Pérez-Patricio, Nestor Antonio Morales Navarro |
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| Rok vydání: | 2018 |
| Předmět: |
2. Zero hunger
Chlorophyll content Scale (ratio) Computer science Applied Mathematics 04 agricultural and veterinary sciences 02 engineering and technology Reflectivity Computer Science Applications Electronic Optical and Magnetic Materials chemistry.chemical_compound chemistry Chlorophyll Linear regression 040103 agronomy & agriculture 0202 electrical engineering electronic engineering information engineering 0401 agriculture forestry and fisheries 020201 artificial intelligence & image processing Smart camera Electrical and Electronic Engineering Field-programmable gate array Remote sensing |
| Zdroj: | International Journal of Circuit Theory and Applications. |
| ISSN: | 0098-9886 |
| DOI: | 10.1002/cta.2489 |
| Popis: | In this work, a new chlorophyll estimation approach based on the reflectance/trans-mittance from the leaf being analyzed is proposed. First, top/underside images from the leaf under analysis are captured, then, the base parameters (reflectance/trans-mittance) are extracted. Finally, a double-variable linear regression model estimates the chlorophyll content. In order to estimate the base parameters, a novel optical arrangement is presented. On the other hand, in order to provide a portable device, suitable for chlorophyll estimation under large scale food crops, we have implemented our optical arrangement and our algorithmic formulation inside an FPGA-based smart camera fabric. Experimental results demonstrated that the proposed approach outperforms (in terms of accuracy and processing speed) most previous vision-based approaches, reaching more than 97% accuracy and delivering fast chlorophyll estimations (near 5ms per estimation). |
| Databáze: | OpenAIRE |
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