Image-Based Identification of Plant Species Using a Model-Free Approach and Active Learning

Grimm J, Hoffmann M, Stöver BC, Müller KF, Steinhage V

Research article (book contribution) | Peer reviewed

Abstract

Collection and maintenance of biodiversity data is in need for automation. We present first results of an automated and model-free approach to the species identification from herbarium specimens kept in herbaria worldwide. Methodologically, our approach relies on standard methods for the detection and description of so-called interest points and their classification into species-characteristic categories using standard supervised learning tools. To keep the approach model-free on the one hand but also offer opportunities for species identification even in very challenging cases on the other hand, we allow to induce specific knowledge about important visual cues by using concepts of active learning on demand. First encouraging results on selected fern species show recognition accuracies between 94 % and 100 %.

Details about the publication

PublisherFriedrich G, Helmert M, Wotawa F
Book titleKI 2016: Advances in Artificial Intelligence
Page range169-176
Publishing companySpringer International Publishing
Title of seriesLecture Notes in Computer Science (ISSN: 0302-9743)
StatusPublished
Release year2016 (26/09/2016)
Language in which the publication is writtenEnglish
DOI10.1007/978-3-319-46073-4_16

Authors from the University of Münster

Müller, Kai
Group Evolution and Biodiversity of Plants (Prof. Müller)
Stöver, Ben
Group Evolution and Biodiversity of Plants (Prof. Müller)