Cargando…

Apple Fruit Recognition Algorithm Based on Multi-Spectral Dynamic Image Analysis

The ability to accurately recognize fruit on trees is a critical step in robotic harvesting. Many researchers have investigated a variety of image analysis methods based on different imaging technologies for fruit recognition. However, challenges still occur in the implementation of this goal due to...

Descripción completa

Detalles Bibliográficos
Autores principales: Feng, Juan, Zeng, Lihua, He, Long
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412272/
https://www.ncbi.nlm.nih.gov/pubmed/30813417
http://dx.doi.org/10.3390/s19040949
_version_ 1783402566777831424
author Feng, Juan
Zeng, Lihua
He, Long
author_facet Feng, Juan
Zeng, Lihua
He, Long
author_sort Feng, Juan
collection PubMed
description The ability to accurately recognize fruit on trees is a critical step in robotic harvesting. Many researchers have investigated a variety of image analysis methods based on different imaging technologies for fruit recognition. However, challenges still occur in the implementation of this goal due to various factors, especially variable light and proximal color background. In this study, images with fruit were acquired with a Forward Looking Infrared (FLIR) camera based on the Multi-Spectral Dynamic Imaging (MSX) technology. In view of its imaging mechanism, the optimal timing and shooting angle for image acquisition were pre-analyzed to obtain the maximum contrast between fruit and background. An effective algorithm was developed for locking potential fruit regions, which was based on the pseudo-color and texture information from MSX images. The algorithm was applied to 506 training and 340 evaluating images, including a variety of fruit and complex backgrounds. Recognition precision and sensitivity of these complete fruit regions were both above 92%, and those of incomplete fruit regions were not lower than 72%. The average processing time for each image was less than 1 s. The results indicated that the developed algorithm based on MSX imaging was effective for fruit recognition and could be suggested as a potential method for the automation of orchard production.
format Online
Article
Text
id pubmed-6412272
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-64122722019-04-03 Apple Fruit Recognition Algorithm Based on Multi-Spectral Dynamic Image Analysis Feng, Juan Zeng, Lihua He, Long Sensors (Basel) Article The ability to accurately recognize fruit on trees is a critical step in robotic harvesting. Many researchers have investigated a variety of image analysis methods based on different imaging technologies for fruit recognition. However, challenges still occur in the implementation of this goal due to various factors, especially variable light and proximal color background. In this study, images with fruit were acquired with a Forward Looking Infrared (FLIR) camera based on the Multi-Spectral Dynamic Imaging (MSX) technology. In view of its imaging mechanism, the optimal timing and shooting angle for image acquisition were pre-analyzed to obtain the maximum contrast between fruit and background. An effective algorithm was developed for locking potential fruit regions, which was based on the pseudo-color and texture information from MSX images. The algorithm was applied to 506 training and 340 evaluating images, including a variety of fruit and complex backgrounds. Recognition precision and sensitivity of these complete fruit regions were both above 92%, and those of incomplete fruit regions were not lower than 72%. The average processing time for each image was less than 1 s. The results indicated that the developed algorithm based on MSX imaging was effective for fruit recognition and could be suggested as a potential method for the automation of orchard production. MDPI 2019-02-23 /pmc/articles/PMC6412272/ /pubmed/30813417 http://dx.doi.org/10.3390/s19040949 Text en © 2019 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
Feng, Juan
Zeng, Lihua
He, Long
Apple Fruit Recognition Algorithm Based on Multi-Spectral Dynamic Image Analysis
title Apple Fruit Recognition Algorithm Based on Multi-Spectral Dynamic Image Analysis
title_full Apple Fruit Recognition Algorithm Based on Multi-Spectral Dynamic Image Analysis
title_fullStr Apple Fruit Recognition Algorithm Based on Multi-Spectral Dynamic Image Analysis
title_full_unstemmed Apple Fruit Recognition Algorithm Based on Multi-Spectral Dynamic Image Analysis
title_short Apple Fruit Recognition Algorithm Based on Multi-Spectral Dynamic Image Analysis
title_sort apple fruit recognition algorithm based on multi-spectral dynamic image analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412272/
https://www.ncbi.nlm.nih.gov/pubmed/30813417
http://dx.doi.org/10.3390/s19040949
work_keys_str_mv AT fengjuan applefruitrecognitionalgorithmbasedonmultispectraldynamicimageanalysis
AT zenglihua applefruitrecognitionalgorithmbasedonmultispectraldynamicimageanalysis
AT helong applefruitrecognitionalgorithmbasedonmultispectraldynamicimageanalysis