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Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems

The application of (smart) cameras for process control, mapping, and advanced imaging in agriculture has become an element of precision farming that facilitates the conservation of fertilizer, pesticides, and machine time. This technique additionally reduces the amount of energy required in terms of...

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Autores principales: Dworak, Volker, Selbeck, Joern, Dammer, Karl-Heinz, Hoffmann, Matthias, Zarezadeh, Ali Akbar, Bobda, Christophe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3649405/
https://www.ncbi.nlm.nih.gov/pubmed/23348037
http://dx.doi.org/10.3390/s130201523
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author Dworak, Volker
Selbeck, Joern
Dammer, Karl-Heinz
Hoffmann, Matthias
Zarezadeh, Ali Akbar
Bobda, Christophe
author_facet Dworak, Volker
Selbeck, Joern
Dammer, Karl-Heinz
Hoffmann, Matthias
Zarezadeh, Ali Akbar
Bobda, Christophe
author_sort Dworak, Volker
collection PubMed
description The application of (smart) cameras for process control, mapping, and advanced imaging in agriculture has become an element of precision farming that facilitates the conservation of fertilizer, pesticides, and machine time. This technique additionally reduces the amount of energy required in terms of fuel. Although research activities have increased in this field, high camera prices reflect low adaptation to applications in all fields of agriculture. Smart, low-cost cameras adapted for agricultural applications can overcome this drawback. The normalized difference vegetation index (NDVI) for each image pixel is an applicable algorithm to discriminate plant information from the soil background enabled by a large difference in the reflectance between the near infrared (NIR) and the red channel optical frequency band. Two aligned charge coupled device (CCD) chips for the red and NIR channel are typically used, but they are expensive because of the precise optical alignment required. Therefore, much attention has been given to the development of alternative camera designs. In this study, the advantage of a smart one-chip camera design with NDVI image performance is demonstrated in terms of low cost and simplified design. The required assembly and pixel modifications are described, and new algorithms for establishing an enhanced NDVI image quality for data processing are discussed.
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spelling pubmed-36494052013-06-04 Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems Dworak, Volker Selbeck, Joern Dammer, Karl-Heinz Hoffmann, Matthias Zarezadeh, Ali Akbar Bobda, Christophe Sensors (Basel) Article The application of (smart) cameras for process control, mapping, and advanced imaging in agriculture has become an element of precision farming that facilitates the conservation of fertilizer, pesticides, and machine time. This technique additionally reduces the amount of energy required in terms of fuel. Although research activities have increased in this field, high camera prices reflect low adaptation to applications in all fields of agriculture. Smart, low-cost cameras adapted for agricultural applications can overcome this drawback. The normalized difference vegetation index (NDVI) for each image pixel is an applicable algorithm to discriminate plant information from the soil background enabled by a large difference in the reflectance between the near infrared (NIR) and the red channel optical frequency band. Two aligned charge coupled device (CCD) chips for the red and NIR channel are typically used, but they are expensive because of the precise optical alignment required. Therefore, much attention has been given to the development of alternative camera designs. In this study, the advantage of a smart one-chip camera design with NDVI image performance is demonstrated in terms of low cost and simplified design. The required assembly and pixel modifications are described, and new algorithms for establishing an enhanced NDVI image quality for data processing are discussed. Molecular Diversity Preservation International (MDPI) 2013-01-24 /pmc/articles/PMC3649405/ /pubmed/23348037 http://dx.doi.org/10.3390/s130201523 Text en © 2013 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Dworak, Volker
Selbeck, Joern
Dammer, Karl-Heinz
Hoffmann, Matthias
Zarezadeh, Ali Akbar
Bobda, Christophe
Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems
title Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems
title_full Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems
title_fullStr Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems
title_full_unstemmed Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems
title_short Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems
title_sort strategy for the development of a smart ndvi camera system for outdoor plant detection and agricultural embedded systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3649405/
https://www.ncbi.nlm.nih.gov/pubmed/23348037
http://dx.doi.org/10.3390/s130201523
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