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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Bibliographic Details
Published in:Journal of imaging 2017-09, Vol.3 (3), p.39
Main Authors: Liu, Suxing, Acosta-Gamboa, Lucia, Huang, Xiuzhen, Lorence, Argelia
Format: Article
Language:English
Subjects:
3D surface model reconstruction
Algorithms
Arabidopsis phenotyping
Barley
Computer vision
Image quality
Image reconstruction
Lasers
Morphology
Motion perception
phenomics
plant phenotyping
Scanners
Sensors
Software
Sorghum
Three dimensional imaging
Three dimensional models
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Summary: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.
ISSN:2313-433X
2313-433X
DOI:10.3390/jimaging3030039