Novel Low Cost 3D Surface Model Reconstruction System for Plant Phenotyping
Accurate high-resolution three-dimensional (3D) models are essential for a non-invasive analysis of phenotypic characteristics of plants. Previous limitations in 3D computer vision algorithms have led to a reliance on volumetric methods or expensive hardware to record plant structure. We present an...
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doaj-e2065b87a69c42b3b1cc9826e187e6682020-11-25T00:08:38ZengMDPI AGJournal of Imaging2313-433X2017-09-01333910.3390/jimaging3030039jimaging3030039Novel Low Cost 3D Surface Model Reconstruction System for Plant PhenotypingSuxing Liu0Lucia M. Acosta-Gamboa1Xiuzhen Huang2Argelia Lorence3Arkansas Biosciences Institute, Arkansas State University, P.O. Box 639, State University, AR 72467, USAArkansas Biosciences Institute, Arkansas State University, P.O. Box 639, State University, AR 72467, USADepartment of Computer Science, Arkansas State University, Jonesboro, AR 72401, USAArkansas Biosciences Institute, Arkansas State University, P.O. Box 639, State University, AR 72467, USAAccurate high-resolution three-dimensional (3D) models are essential for a non-invasive analysis of phenotypic characteristics of plants. Previous limitations in 3D computer vision algorithms have led to a reliance on volumetric methods or expensive hardware to record plant structure. We present an image-based 3D plant reconstruction system that can be achieved by using a single camera and a rotation stand. Our method is based on the structure from motion method, with a SIFT image feature descriptor. In order to improve the quality of the 3D models, we segmented the plant objects based on the PlantCV platform. We also deducted the optimal number of images needed for reconstructing a high-quality model. Experiments showed that an accurate 3D model of the plant was successfully could be reconstructed by our approach. This 3D surface model reconstruction system provides a simple and accurate computational platform for non-destructive, plant phenotyping.https://www.mdpi.com/2313-433X/3/3/393D surface model reconstructionplant phenotypingphenomicsArabidopsis phenotyping |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Suxing Liu Lucia M. Acosta-Gamboa Xiuzhen Huang Argelia Lorence |
spellingShingle |
Suxing Liu Lucia M. Acosta-Gamboa Xiuzhen Huang Argelia Lorence Novel Low Cost 3D Surface Model Reconstruction System for Plant Phenotyping Journal of Imaging 3D surface model reconstruction plant phenotyping phenomics Arabidopsis phenotyping |
author_facet |
Suxing Liu Lucia M. Acosta-Gamboa Xiuzhen Huang Argelia Lorence |
author_sort |
Suxing Liu |
title |
Novel Low Cost 3D Surface Model Reconstruction System for Plant Phenotyping |
title_short |
Novel Low Cost 3D Surface Model Reconstruction System for Plant Phenotyping |
title_full |
Novel Low Cost 3D Surface Model Reconstruction System for Plant Phenotyping |
title_fullStr |
Novel Low Cost 3D Surface Model Reconstruction System for Plant Phenotyping |
title_full_unstemmed |
Novel Low Cost 3D Surface Model Reconstruction System for Plant Phenotyping |
title_sort |
novel low cost 3d surface model reconstruction system for plant phenotyping |
publisher |
MDPI AG |
series |
Journal of Imaging |
issn |
2313-433X |
publishDate |
2017-09-01 |
description |
Accurate high-resolution three-dimensional (3D) models are essential for a non-invasive analysis of phenotypic characteristics of plants. Previous limitations in 3D computer vision algorithms have led to a reliance on volumetric methods or expensive hardware to record plant structure. We present an image-based 3D plant reconstruction system that can be achieved by using a single camera and a rotation stand. Our method is based on the structure from motion method, with a SIFT image feature descriptor. In order to improve the quality of the 3D models, we segmented the plant objects based on the PlantCV platform. We also deducted the optimal number of images needed for reconstructing a high-quality model. Experiments showed that an accurate 3D model of the plant was successfully could be reconstructed by our approach. This 3D surface model reconstruction system provides a simple and accurate computational platform for non-destructive, plant phenotyping. |
topic |
3D surface model reconstruction plant phenotyping phenomics Arabidopsis phenotyping |
url |
https://www.mdpi.com/2313-433X/3/3/39 |
work_keys_str_mv |
AT suxingliu novellowcost3dsurfacemodelreconstructionsystemforplantphenotyping AT luciamacostagamboa novellowcost3dsurfacemodelreconstructionsystemforplantphenotyping AT xiuzhenhuang novellowcost3dsurfacemodelreconstructionsystemforplantphenotyping AT argelialorence novellowcost3dsurfacemodelreconstructionsystemforplantphenotyping |
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1725415222999515136 |