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Automatic detection of diseased tomato plants using thermal and stereo visible light images

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Raza, Shan-e-Ahmed, Prince, Gillian, Clarkson, John P. and Rajpoot, Nasir M. (2015) Automatic detection of diseased tomato plants using thermal and stereo visible light images. PLoS One, Volume 10 (Number 4). Article number e0123262. doi:10.1371/journal.pone.0123262

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Official URL: http://dx.doi.org/10.1371/journal.pone.0123262

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Abstract

Accurate and timely detection of plant diseases can help mitigate the worldwide losses experienced by the horticulture and agriculture industries each year. Thermal imaging provides a fast and non-destructive way of scanning plants for diseased regions and has been used by various researchers to study the effect of disease on the thermal profile of a plant. However, thermal image of a plant affected by disease has been known to be affected by environmental conditions which include leaf angles and depth of the canopy areas accessible to the thermal imaging camera. In this paper, we combine thermal and visible light image data with depth information and develop a machine learning system to remotely detect plants infected with the tomato powdery mildew fungus Oidium neolycopersici. We extract a novel feature set from the image data using local and global statistics and show that by combining these with the depth information, we can considerably improve the accuracy of detection of the diseased plants. In addition, we show that our novel feature set is capable of identifying plants which were not originally inoculated with the fungus at the start of the experiment but which subsequently developed disease through natural transmission.

Item Type: Journal Article
Subjects: Q Science > QK Botany
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- )
Library of Congress Subject Headings (LCSH): Plant diseases -- Imaging, Infrared imaging, Tomatoes -- Diseases and pests, Powdery mildew diseases
Journal or Publication Title: PLoS One
Publisher: Public Library of Science
ISSN: 1932-6203
Official Date: 10 April 2015
Dates:
DateEvent
10 April 2015Published
17 February 2015Accepted
9 September 2014Submitted
Volume: Volume 10
Number: Number 4
Article Number: Article number e0123262
DOI: 10.1371/journal.pone.0123262
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
Funder: Horticultural Development Company, University of Warwick. Department of Computer Science, Engineering and Physical Sciences Research Council (EPSRC)
Grant number: CP60a (DCS)

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