Cargando…

Automated plant species identification—Trends and future directions

Current rates of species loss triggered numerous attempts to protect and conserve biodiversity. Species conservation, however, requires species identification skills, a competence obtained through intensive training and experience. Field researchers, land managers, educators, civil servants, and the...

Descripción completa

Detalles Bibliográficos
Autores principales: Wäldchen, Jana, Rzanny, Michael, Seeland, Marco, Mäder, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5886388/
https://www.ncbi.nlm.nih.gov/pubmed/29621236
http://dx.doi.org/10.1371/journal.pcbi.1005993
_version_ 1783312119673913344
author Wäldchen, Jana
Rzanny, Michael
Seeland, Marco
Mäder, Patrick
author_facet Wäldchen, Jana
Rzanny, Michael
Seeland, Marco
Mäder, Patrick
author_sort Wäldchen, Jana
collection PubMed
description Current rates of species loss triggered numerous attempts to protect and conserve biodiversity. Species conservation, however, requires species identification skills, a competence obtained through intensive training and experience. Field researchers, land managers, educators, civil servants, and the interested public would greatly benefit from accessible, up-to-date tools automating the process of species identification. Currently, relevant technologies, such as digital cameras, mobile devices, and remote access to databases, are ubiquitously available, accompanied by significant advances in image processing and pattern recognition. The idea of automated species identification is approaching reality. We review the technical status quo on computer vision approaches for plant species identification, highlight the main research challenges to overcome in providing applicable tools, and conclude with a discussion of open and future research thrusts.
format Online
Article
Text
id pubmed-5886388
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-58863882018-04-20 Automated plant species identification—Trends and future directions Wäldchen, Jana Rzanny, Michael Seeland, Marco Mäder, Patrick PLoS Comput Biol Review Current rates of species loss triggered numerous attempts to protect and conserve biodiversity. Species conservation, however, requires species identification skills, a competence obtained through intensive training and experience. Field researchers, land managers, educators, civil servants, and the interested public would greatly benefit from accessible, up-to-date tools automating the process of species identification. Currently, relevant technologies, such as digital cameras, mobile devices, and remote access to databases, are ubiquitously available, accompanied by significant advances in image processing and pattern recognition. The idea of automated species identification is approaching reality. We review the technical status quo on computer vision approaches for plant species identification, highlight the main research challenges to overcome in providing applicable tools, and conclude with a discussion of open and future research thrusts. Public Library of Science 2018-04-05 /pmc/articles/PMC5886388/ /pubmed/29621236 http://dx.doi.org/10.1371/journal.pcbi.1005993 Text en © 2018 Wäldchen et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Review
Wäldchen, Jana
Rzanny, Michael
Seeland, Marco
Mäder, Patrick
Automated plant species identification—Trends and future directions
title Automated plant species identification—Trends and future directions
title_full Automated plant species identification—Trends and future directions
title_fullStr Automated plant species identification—Trends and future directions
title_full_unstemmed Automated plant species identification—Trends and future directions
title_short Automated plant species identification—Trends and future directions
title_sort automated plant species identification—trends and future directions
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5886388/
https://www.ncbi.nlm.nih.gov/pubmed/29621236
http://dx.doi.org/10.1371/journal.pcbi.1005993
work_keys_str_mv AT waldchenjana automatedplantspeciesidentificationtrendsandfuturedirections
AT rzannymichael automatedplantspeciesidentificationtrendsandfuturedirections
AT seelandmarco automatedplantspeciesidentificationtrendsandfuturedirections
AT maderpatrick automatedplantspeciesidentificationtrendsandfuturedirections