Cargando…
Date fruit dataset for intelligent harvesting
The date palm is one of the most valuable fruit trees in the world. Most methods used for date fruit inspection, harvesting, grading, and classification are manual, which makes them ineffective in terms of both time and economy. Research on automated date fruit harvesting is limited as there is no p...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811983/ https://www.ncbi.nlm.nih.gov/pubmed/31667277 http://dx.doi.org/10.1016/j.dib.2019.104514 |
_version_ | 1783462577960910848 |
---|---|
author | Altaheri, Hamdi Alsulaiman, Mansour Muhammad, Ghulam Amin, Syed Umar Bencherif, Mohamed Mekhtiche, Mohamed |
author_facet | Altaheri, Hamdi Alsulaiman, Mansour Muhammad, Ghulam Amin, Syed Umar Bencherif, Mohamed Mekhtiche, Mohamed |
author_sort | Altaheri, Hamdi |
collection | PubMed |
description | The date palm is one of the most valuable fruit trees in the world. Most methods used for date fruit inspection, harvesting, grading, and classification are manual, which makes them ineffective in terms of both time and economy. Research on automated date fruit harvesting is limited as there is no public dataset for date fruits to aid in this. In this work, we present a comprehensive dataset for date fruits that can be used by the research community for multiple tasks including automated harvesting, visual yield estimation, and classification tasks. The dataset contains images of date fruit bunches of different date varieties, captured at different pre-maturity and maturity stages. These images cover multiple sets of variations such as multi-scale images, variable illumination, and different bagging states. We also marked date bunches for selected palms and measured the weights of the bunches, captured their images on a graph paper, and recorded 360° video of the palms. This dataset can help in advancing research and automating date palm agricultural applications, including robotic harvesting, fruit detection and classification, maturity analysis, and weight/yield estimation. The dataset is freely and publicly available for the research community in the IEEE DataPort repository [1] (https://doi.org/10.21227/x46j-sk98). |
format | Online Article Text |
id | pubmed-6811983 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-68119832019-10-30 Date fruit dataset for intelligent harvesting Altaheri, Hamdi Alsulaiman, Mansour Muhammad, Ghulam Amin, Syed Umar Bencherif, Mohamed Mekhtiche, Mohamed Data Brief Computer Science The date palm is one of the most valuable fruit trees in the world. Most methods used for date fruit inspection, harvesting, grading, and classification are manual, which makes them ineffective in terms of both time and economy. Research on automated date fruit harvesting is limited as there is no public dataset for date fruits to aid in this. In this work, we present a comprehensive dataset for date fruits that can be used by the research community for multiple tasks including automated harvesting, visual yield estimation, and classification tasks. The dataset contains images of date fruit bunches of different date varieties, captured at different pre-maturity and maturity stages. These images cover multiple sets of variations such as multi-scale images, variable illumination, and different bagging states. We also marked date bunches for selected palms and measured the weights of the bunches, captured their images on a graph paper, and recorded 360° video of the palms. This dataset can help in advancing research and automating date palm agricultural applications, including robotic harvesting, fruit detection and classification, maturity analysis, and weight/yield estimation. The dataset is freely and publicly available for the research community in the IEEE DataPort repository [1] (https://doi.org/10.21227/x46j-sk98). Elsevier 2019-09-18 /pmc/articles/PMC6811983/ /pubmed/31667277 http://dx.doi.org/10.1016/j.dib.2019.104514 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Computer Science Altaheri, Hamdi Alsulaiman, Mansour Muhammad, Ghulam Amin, Syed Umar Bencherif, Mohamed Mekhtiche, Mohamed Date fruit dataset for intelligent harvesting |
title | Date fruit dataset for intelligent harvesting |
title_full | Date fruit dataset for intelligent harvesting |
title_fullStr | Date fruit dataset for intelligent harvesting |
title_full_unstemmed | Date fruit dataset for intelligent harvesting |
title_short | Date fruit dataset for intelligent harvesting |
title_sort | date fruit dataset for intelligent harvesting |
topic | Computer Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811983/ https://www.ncbi.nlm.nih.gov/pubmed/31667277 http://dx.doi.org/10.1016/j.dib.2019.104514 |
work_keys_str_mv | AT altaherihamdi datefruitdatasetforintelligentharvesting AT alsulaimanmansour datefruitdatasetforintelligentharvesting AT muhammadghulam datefruitdatasetforintelligentharvesting AT aminsyedumar datefruitdatasetforintelligentharvesting AT bencherifmohamed datefruitdatasetforintelligentharvesting AT mekhtichemohamed datefruitdatasetforintelligentharvesting |