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About the Authors:
Jana Wäldchen
* E-mail: [email protected]
Affiliation: Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Thuringia, Germany
ORCID http://orcid.org/0000-0002-2631-1531
Michael Rzanny
Affiliation: Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Thuringia, Germany
Marco Seeland
Affiliation: Software Engineering for Safety-Critical Systems Group, Technische Universität Ilmenau, Ilmenau, Thuringia, Germany
ORCID http://orcid.org/0000-0001-7204-3972
Patrick Mäder
Affiliation: Software Engineering for Safety-Critical Systems Group, Technische Universität Ilmenau, Ilmenau, Thuringia, GermanyAbstract
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.
Author summary
Plant identification is not exclusively the job of botanists and plant ecologists. It is required or useful for large parts of society, from professionals (such as landscape architects, foresters, farmers, conservationists, and biologists) to the general public (like ecotourists, hikers, and nature lovers). But the identification of plants by conventional means is difficult, time consuming, and (due to the use of specific botanical terms) frustrating for novices. This creates a hard-to-overcome hurdle for novices interested in acquiring species knowledge. In recent years, computer science research, especially image processing and pattern recognition techniques, have been introduced into plant taxonomy to eventually make up for the deficiency in people's identification abilities. 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.
Citation: Wäldchen J, Rzanny M, Seeland M, Mäder P (2018) Automated plant species identification-Trends and future directions. PLoS Comput Biol 14(4): e1005993. https://doi.org/10.1371/journal.pcbi.1005993
Editor: Alexander Bucksch, University of Georgia Warnell School of Forestry and...