An approach to detect branches and seedpods based on 3D image in low-cost plant phenotyping platform

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  1. Available on June 15, 2018
DOIResolve DOI: http://doi.org/10.1109/CCECE.2017.7946593
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TypeArticle
Proceedings title2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE)
ConferenceIEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE), 30 April-3 May 2017, Windsor, ON, Canada
ISBN9781509055388
Article number16963524
Subject3D plant phenotyping; image processing; time-of-flight camera; counting branches and seedpods
AbstractTo meet the high demand for supporting and accelerating progress in breeding of novel traits, plant scientists and breeders have to make more efforts to deal with the need to accurately measure a large number of plants and their characteristics. A variety of imaging methodologies is being deployed to acquire data for quantitative studies of complex traits. When applied to a large number of plants, however, a complete 3D model is very time-consuming for high-throughput phenotyping with an enormous amount of data. In some contexts, complete rebuild of entire plants may not be necessary. With the aim of producing a smaller amount of data per plant, low-cost depth imaging systems can be useful. We propose the use of such a low-cost depth camera, called Time-of-Flight (ToF), to have videos and pictures of the plant in 3D. An application has been developed to display 3D model of a plant and estimate certain characteristics. Counting the number of branches and seedpods of the canola plant have been implemented. Estimating the biomass and crop yield will be deployed in the near future.
Publication date
PublisherIEEE
LanguageEnglish
AffiliationNational Research Council Canada; Aquatic and Crop Resource Development
Peer reviewedYes
NRC numberNRC-ACRD-56317
NPARC number23002104
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Record identifier953390a1-7621-4dc9-8faa-2d3da061aa78
Record created2017-08-18
Record modified2017-08-22
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