A hybrid approach for improving image segmentation: Application to phenotyping of wheat leaves

J. Chopin; H. Laga; S.J. Miklavcic

doi:10.1371/journal.pone.0168496

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A hybrid approach for improving image segmentation: Application to phenotyping of wheat leaves

Journal article

Open access

Peer reviewed

A hybrid approach for improving image segmentation: Application to phenotyping of wheat leaves

J. Chopin, H. Laga and S.J. Miklavcic

PloS one, Vol.11(12), e0168496

2016

DOI: https://doi.org/10.1371/journal.pone.0168496

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Abstract

In this article we propose a novel tool that takes an initial segmented image and returns a more accurate segmentation that accurately captures sharp features such as leaf tips, twists and axils. Our algorithm utilizes basic a-priori information about the shape of plant leaves and local image orientations to fit active contour models to important plant features that have been missed during the initial segmentation. We compare the performance of our approach with three state-of-the-art segmentation techniques, using three error metrics. The results show that leaf tips are detected with roughly one half of the original error, segmentation accuracy is almost always improved and more than half of the leaf breakages are corrected.

Details

Title: A hybrid approach for improving image segmentation: Application to phenotyping of wheat leaves
Authors/Creators: J. Chopin (Author/Creator) - University of South Australia
H. Laga (Author/Creator) - Murdoch University
S.J. Miklavcic (Author/Creator) - University of South Australia
Publication Details: PloS one, Vol.11(12), e0168496
Publisher: Public Library of Science
Identifiers: 991005541756707891
Copyright: © 2016 Chopin et al.
Murdoch Affiliation: School of Engineering and Information Technology
Language: English
Resource Type: Journal article

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Collaboration types: Domestic collaboration
Citation topics: 4 Electrical Engineering, Electronics & Computer Science; 4.17 Computer Vision & Graphics; 4.17.282 Image Segmentation
Web Of Science research areas: Engineering, Electrical & Electronic
ESI research areas: Engineering