Cargando…
In Field Fruit Sizing Using A Smart Phone Application
In field (on tree) fruit sizing has value in assessing crop health and for yield estimation. As the mobile phone is a sensor and communication rich device carried by almost all farm staff, an Android application (“FruitSize”) was developed for measurement of fruit size in field using the phone camer...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6210956/ https://www.ncbi.nlm.nih.gov/pubmed/30301141 http://dx.doi.org/10.3390/s18103331 |
_version_ | 1783367233388412928 |
---|---|
author | Wang, Zhenglin Koirala, Anand Walsh, Kerry Anderson, Nicholas Verma, Brijesh |
author_facet | Wang, Zhenglin Koirala, Anand Walsh, Kerry Anderson, Nicholas Verma, Brijesh |
author_sort | Wang, Zhenglin |
collection | PubMed |
description | In field (on tree) fruit sizing has value in assessing crop health and for yield estimation. As the mobile phone is a sensor and communication rich device carried by almost all farm staff, an Android application (“FruitSize”) was developed for measurement of fruit size in field using the phone camera, with a typical assessment rate of 240 fruit per hour achieved. The application was based on imaging of fruit against a backboard with a scale using a mobile phone, with operational limits set on camera to object plane angle and camera to object distance. Image processing and object segmentation techniques available in the OpenCV library were used to segment the fruit from background in images to obtain fruit sizes. Phone camera parameters were accessed to allow calculation of fruit size, with camera to fruit perimeter distance obtained from fruit allometric relationships between fruit thickness and width. Phone geolocation data was also accessed, allowing for mapping fruits of data. Under controlled lighting, RMSEs of 3.4, 3.8, 2.4, and 2.0 mm were achieved in estimation of avocado, mandarin, navel orange, and apple fruit diameter, respectively. For mango fruit, RMSEs of 5.3 and 3.7 mm were achieved on length and width, benchmarked to manual caliper measurements, under controlled lighting, and RMSEs of 5.5 and 4.6 mm were obtained in-field under ambient lighting. |
format | Online Article Text |
id | pubmed-6210956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-62109562018-11-02 In Field Fruit Sizing Using A Smart Phone Application Wang, Zhenglin Koirala, Anand Walsh, Kerry Anderson, Nicholas Verma, Brijesh Sensors (Basel) Technical Note In field (on tree) fruit sizing has value in assessing crop health and for yield estimation. As the mobile phone is a sensor and communication rich device carried by almost all farm staff, an Android application (“FruitSize”) was developed for measurement of fruit size in field using the phone camera, with a typical assessment rate of 240 fruit per hour achieved. The application was based on imaging of fruit against a backboard with a scale using a mobile phone, with operational limits set on camera to object plane angle and camera to object distance. Image processing and object segmentation techniques available in the OpenCV library were used to segment the fruit from background in images to obtain fruit sizes. Phone camera parameters were accessed to allow calculation of fruit size, with camera to fruit perimeter distance obtained from fruit allometric relationships between fruit thickness and width. Phone geolocation data was also accessed, allowing for mapping fruits of data. Under controlled lighting, RMSEs of 3.4, 3.8, 2.4, and 2.0 mm were achieved in estimation of avocado, mandarin, navel orange, and apple fruit diameter, respectively. For mango fruit, RMSEs of 5.3 and 3.7 mm were achieved on length and width, benchmarked to manual caliper measurements, under controlled lighting, and RMSEs of 5.5 and 4.6 mm were obtained in-field under ambient lighting. MDPI 2018-10-05 /pmc/articles/PMC6210956/ /pubmed/30301141 http://dx.doi.org/10.3390/s18103331 Text en © 2018 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 | Technical Note Wang, Zhenglin Koirala, Anand Walsh, Kerry Anderson, Nicholas Verma, Brijesh In Field Fruit Sizing Using A Smart Phone Application |
title | In Field Fruit Sizing Using A Smart Phone Application |
title_full | In Field Fruit Sizing Using A Smart Phone Application |
title_fullStr | In Field Fruit Sizing Using A Smart Phone Application |
title_full_unstemmed | In Field Fruit Sizing Using A Smart Phone Application |
title_short | In Field Fruit Sizing Using A Smart Phone Application |
title_sort | in field fruit sizing using a smart phone application |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6210956/ https://www.ncbi.nlm.nih.gov/pubmed/30301141 http://dx.doi.org/10.3390/s18103331 |
work_keys_str_mv | AT wangzhenglin infieldfruitsizingusingasmartphoneapplication AT koiralaanand infieldfruitsizingusingasmartphoneapplication AT walshkerry infieldfruitsizingusingasmartphoneapplication AT andersonnicholas infieldfruitsizingusingasmartphoneapplication AT vermabrijesh infieldfruitsizingusingasmartphoneapplication |