Abstract
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.
Highlights
One of the most obvious features of organic life is its remarkable diversity [1]
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
This article focuses on plant identification, which is the process of assigning an individual plant to a taxon based on the resemblance of discriminatory and morphological plant characters, arriving at a species or infraspecific name
Summary
Editor: Alexander Bucksch, University of Georgia Warnell School of Forestry and Natural Resources, UNITED STATES. De/); the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB) grant: 3514 685C19 (https://www.bmub.bund.de/); and the Stiftung Naturschutz Thuringen (SNT) grant: SNT-082-24803/2014 (http://www.stiftung-naturschutzthueringen.de/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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