Extracting Phenotypic Characteristics of Corn Crops Through the Use of Reconstructed 3D Models

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Financial and social elements of modern societies are closely connected to the cultivation of corn. Due to its massive production, deficiencies during the cultivation process directly translate to major financial losses. Since proper surveillance in a large scale is still very challenging, the companies that specialize in optimizing crop yield are trying to address the problem at its root by developing hybrid plants able to resist the harsh conditions of the field. The selection of the best hybrid is not easy and every year hundreds of test plants with different phenotypic characteristics are planted while their performance is quantified by inconsistent and rough measurements gathered by humans. We propose a pipeline that takes advantage of the structure from motion technology to create a detailed 3D point cloud of a few plants and segment it into the basic elements of the scene; the ground, the plants, the plant stems, and the plant leaves. The focus is on the segmentation process through which several phenotypic characteristics of individual plants can be extracted. As an example, we show the results for the plant counting and plant height estimation processes where we achieve an accuracy of 88.1 % and 89.2%.

Original languageEnglish (US)
Title of host publication2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages8247-8254
Number of pages8
ISBN (Electronic)9781538680940
DOIs
StatePublished - Dec 27 2018
Event2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018 - Madrid, Spain
Duration: Oct 1 2018Oct 5 2018

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
CountrySpain
CityMadrid
Period10/1/1810/5/18

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Zermas, D., Morellas, V., Mulla, D. J., & Papanikolopoulos, N. P. (2018). Extracting Phenotypic Characteristics of Corn Crops Through the Use of Reconstructed 3D Models. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018 (pp. 8247-8254). [8594356] (IEEE International Conference on Intelligent Robots and Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS.2018.8594356