Automated recovery of 3D models of plant shoots from multiple colour images

Pound, Michael P. and French, Andrew P. and Murchie, Erik H. and Pridmore, Tony P. (2014) Automated recovery of 3D models of plant shoots from multiple colour images. Plant Physiology, 166 (4). pp. 1688-1698. ISSN 0032-0889

[img]
Preview
PDF (Manuscript) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (8MB) | Preview

Abstract

Increased adoption of the systems approach to biological research has focussed attention on the use of quantitative models of biological objects. This includes a need for realistic 3D representations of plant shoots for quantification and modelling. Previous limitations in single or multi-view stereo algorithms have led to a reliance on volumetric methods or expensive hardware to record plant structure. We present a fully automatic approach to image-based 3D plant reconstruction that can be achieved using a single low-cost camera. The reconstructed plants are represented as a series of small planar sections that together model the more complex architecture of the leaf surfaces. The boundary of each leaf patch is refined using the level set method, optimising the model based on image information, curvature constraints and the position of neighbouring surfaces. The reconstruction process makes few assumptions about the nature of the plant material being reconstructed, and as such is applicable to a wide variety of plant species and topologies, and can be extended to canopy-scale imaging. We demonstrate the effectiveness of our approach on datasets of wheat and rice plants, as well as a novel virtual dataset that allows us to compute quantitative measures of reconstruction accuracy. The output is a 3D mesh structure that is suitable for modelling applications, in a format that can be imported in the majority of 3D graphics and software packages.

Item Type: Article
Schools/Departments: University of Nottingham UK Campus > Faculty of Science > School of Biosciences > Division of Plant and Crop Sciences
University of Nottingham UK Campus > Faculty of Science > School of Computer Science
Identification Number: doi:​​10.1104/pp.114.248971
Depositing User: Pound, Michael
Date Deposited: 25 Jun 2015 13:32
Last Modified: 14 Sep 2016 03:45
URI: http://eprints.nottingham.ac.uk/id/eprint/29219

Actions (Archive Staff Only)

Edit View Edit View