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A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops
Crop monitoring is an essential practice within the field of precision agriculture since it is based on observing, measuring and properly responding to inter- and intra-field variability. In particular, “on ground crop inspection” potentially allows early detection of certain crop problems or precis...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795857/ https://www.ncbi.nlm.nih.gov/pubmed/29295536 http://dx.doi.org/10.3390/s18010030 |
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author | Bengochea-Guevara, José M. Andújar, Dionisio Sanchez-Sardana, Francisco L. Cantuña, Karla Ribeiro, Angela |
author_facet | Bengochea-Guevara, José M. Andújar, Dionisio Sanchez-Sardana, Francisco L. Cantuña, Karla Ribeiro, Angela |
author_sort | Bengochea-Guevara, José M. |
collection | PubMed |
description | Crop monitoring is an essential practice within the field of precision agriculture since it is based on observing, measuring and properly responding to inter- and intra-field variability. In particular, “on ground crop inspection” potentially allows early detection of certain crop problems or precision treatment to be carried out simultaneously with pest detection. “On ground monitoring” is also of great interest for woody crops. This paper explores the development of a low-cost crop monitoring system that can automatically create accurate 3D models (clouds of coloured points) of woody crop rows. The system consists of a mobile platform that allows the easy acquisition of information in the field at an average speed of 3 km/h. The platform, among others, integrates an RGB-D sensor that provides RGB information as well as an array with the distances to the objects closest to the sensor. The RGB-D information plus the geographical positions of relevant points, such as the starting and the ending points of the row, allow the generation of a 3D reconstruction of a woody crop row in which all the points of the cloud have a geographical location as well as the RGB colour values. The proposed approach for the automatic 3D reconstruction is not limited by the size of the sampled space and includes a method for the removal of the drift that appears in the reconstruction of large crop rows. |
format | Online Article Text |
id | pubmed-5795857 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-57958572018-02-13 A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops Bengochea-Guevara, José M. Andújar, Dionisio Sanchez-Sardana, Francisco L. Cantuña, Karla Ribeiro, Angela Sensors (Basel) Article Crop monitoring is an essential practice within the field of precision agriculture since it is based on observing, measuring and properly responding to inter- and intra-field variability. In particular, “on ground crop inspection” potentially allows early detection of certain crop problems or precision treatment to be carried out simultaneously with pest detection. “On ground monitoring” is also of great interest for woody crops. This paper explores the development of a low-cost crop monitoring system that can automatically create accurate 3D models (clouds of coloured points) of woody crop rows. The system consists of a mobile platform that allows the easy acquisition of information in the field at an average speed of 3 km/h. The platform, among others, integrates an RGB-D sensor that provides RGB information as well as an array with the distances to the objects closest to the sensor. The RGB-D information plus the geographical positions of relevant points, such as the starting and the ending points of the row, allow the generation of a 3D reconstruction of a woody crop row in which all the points of the cloud have a geographical location as well as the RGB colour values. The proposed approach for the automatic 3D reconstruction is not limited by the size of the sampled space and includes a method for the removal of the drift that appears in the reconstruction of large crop rows. MDPI 2017-12-24 /pmc/articles/PMC5795857/ /pubmed/29295536 http://dx.doi.org/10.3390/s18010030 Text en © 2017 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Bengochea-Guevara, José M. Andújar, Dionisio Sanchez-Sardana, Francisco L. Cantuña, Karla Ribeiro, Angela A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops |
title | A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops |
title_full | A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops |
title_fullStr | A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops |
title_full_unstemmed | A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops |
title_short | A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops |
title_sort | low-cost approach to automatically obtain accurate 3d models of woody crops |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795857/ https://www.ncbi.nlm.nih.gov/pubmed/29295536 http://dx.doi.org/10.3390/s18010030 |
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