Developing a low-cost 3D plant morphological traits characterization system

dc.contributor.author Li, Ji
dc.contributor.author Tang, Lie
dc.contributor.author Tang, Lie
dc.contributor.department Agricultural and Biosystems Engineering
dc.contributor.department Human Computer Interaction
dc.contributor.department Plant Sciences Institute
dc.date 2019-12-10T20:15:46.000
dc.date.accessioned 2020-06-29T22:36:33Z
dc.date.available 2020-06-29T22:36:33Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.issued 2017-12-01
dc.description.abstract <p>A low-cost three-dimensional (3D) plant reconstruction and morphological traits characterization system was developed. Corn plant seedlings were used as research objects for development and validation of the 3D reconstruction and point cloud data analysis algorithms. In this application, precise alignment of multiple 3D views generated by a 3D time-of-flight (ToF) sensor is critical to the 3D reconstruction of a plant. Previous research indicated that there is strong need for high-throughput, high-accuracy, and low-cost 3D plant reconstruction and trait characterization phenotyping systems. This research produced a 3D reconstruction system for indoor plant phenotyping by innovatively integrating a low-cost 2D camera, a low-cost 3D ToF camera, and a chessboard pattern beacon array to track the position and attitude of the 3D ToF sensor and, thus, accomplished precise 3D point cloud registration over multiple views. Specifically, algorithms for beacon target detection, camera pose tracking, and spatial relationship calibration between 2D and 3D cameras were developed for such a low-cost but high-performance 3D reconstruction solution. A plant analysis algorithm in a 3D space was developed to extract the morphological trait parameters of the plants by analyzing their 3D point cloud data. The phenotypical data obtained by this novel and low-cost 3D reconstruction based phenotyping system were validated by the experimental data generated by instrument and manual measurement. The results demonstrated that the developed phenotyping system has achieved promising measurement accuracy, fast processing speed while offering a low hardware cost, lending itself to a practical means of acquiring detailed 3D morphological traits for automated indoor plant phenotyping.</p>
dc.description.comments <p>This is a manuscript of an article published as Li, Ji, and Lie Tang. "Developing a low-cost 3D plant morphological traits characterization system." <em>Computers and Electronics in Agriculture</em> 143 (2017): 1-13. DOI: <a href="http://dx.doi.org/10.1016/j.compag.2017.09.025" target="_blank">10.1016/j.compag.2017.09.025</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/abe_eng_pubs/1058/
dc.identifier.articleid 2348
dc.identifier.contextkey 15362342
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath abe_eng_pubs/1058
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/760
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/abe_eng_pubs/1058/2017_TangLie_DevelopingLow.pdf|||Fri Jan 14 18:23:45 UTC 2022
dc.source.uri 10.1016/j.compag.2017.09.025
dc.subject.disciplines Agriculture
dc.subject.disciplines Bioresource and Agricultural Engineering
dc.subject.keywords Plant phenotyping
dc.subject.keywords 3D reconstruction
dc.subject.keywords Machine vision
dc.subject.keywords Chessboard pattern beacon
dc.subject.keywords Camera localization
dc.title Developing a low-cost 3D plant morphological traits characterization system
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication e60e10a5-8712-462a-be4b-f486a3461aea
relation.isOrgUnitOfPublication 8eb24241-0d92-4baf-ae75-08f716d30801
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