Please use this identifier to cite or link to this item:
Type: Conference paper
Title: Gaussian mixture models for image-based cereal plant canopy analysis
Author: Laga, H.
Kumar, P.
Cai, J.
Haefele, S.
Anbalagan, R.
Kovalchuk, N.
Miklavcic, S.
Citation: Proceeding of the 21st International Congress on Modelling and Simulation, 2015 / Weber, T., McPhee, M., Anderssen, R. (ed./s), pp.510-516
Publisher: The Modelling and Simulation Society of Aust & NZ
Issue Date: 2015
ISBN: 9780987214355
Conference Name: 21st International Congress on Modelling and Simulation (MODSIM2015) (29 Nov 2015 - 4 Dec 2015 : Broadbeach, Queensland)
Editor: Weber, T.
McPhee, M.
Anderssen, R.
Statement of
Hamid Laga, Pankaj Kumar, Jinhai Cai, Stephan Haefele, Raghu Anbalagan, Nataliya Kovalchuk, Stanley J. Miklavcic
Abstract: In this paper, we report our results of applying Gaussian Mixture Models (GMM) to the analysis of the canopy of cereal plants grown in competitive environments, such as large bins. We will particularly focus on the segmentation problem, i.e. separating the plant regions from the other image regions, such as soil, water pipes, and bin walls. We will show that GMMs, which require few training images, provide a flexible and efficient tool for high throughput segmentation at various growth stages and even in the presence of complex background. We discuss various implementation issues and provide results on a large scale experiment, where cereal plants of different genotypes are grown in large bins and subject to two different treatments (well watered and under drought stress).
Keywords: Plant phenotyping; canopy coverage; plant growth analysis
Description: Session: Biological systems B6. Mathematical modelling and image analysis for plant phenotyping
Rights: Copyright © 2015 The Modelling and Simulation Society of Australia and New Zealand Inc. All rights reserved.
Published version:
Appears in Collections:Agriculture, Food and Wine publications
Aurora harvest 3

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.