Automated plant species identification-Trends and future directions

PLoS Comput Biol. 2018 Apr 5;14(4):e1005993. doi: 10.1371/journal.pcbi.1005993. eCollection 2018 Apr.

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.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Artificial Intelligence
  • Biodiversity
  • Computational Biology
  • Conservation of Natural Resources
  • Flowers / anatomy & histology
  • Flowers / classification
  • Image Processing, Computer-Assisted / methods
  • Image Processing, Computer-Assisted / trends
  • Pattern Recognition, Automated / methods*
  • Pattern Recognition, Automated / trends
  • Pigmentation
  • Plant Leaves / anatomy & histology
  • Plant Leaves / classification
  • Plants / anatomy & histology*
  • Plants / classification*
  • Supervised Machine Learning

Grants and funding

We are funded by the German Ministry of Education and Research (BMBF) grants: 01LC1319A and 01LC1319B (https://www.bmbf.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 Thüringen (SNT) grant: SNT-082-248-03/2014 (http://www.stiftung-naturschutz-thueringen.de/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.