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An automatic segmentation method for scanned images of wheat root systems with dark discolourations Cover

An automatic segmentation method for scanned images of wheat root systems with dark discolourations

Open Access
|Dec 2009

Abstract

The analysis of plant root system images plays an important role in the diagnosis of plant health state, the detection of possible diseases and growth distortions. This paper describes an initial stage of automatic analysis—the segmentation method for scanned images of Ni-treated wheat roots from hydroponic culture. The main roots of a wheat fibrous system are placed separately in the scanner view area on a high chroma background (blue or red). The first stage of the method includes the transformation of a scanned RGB image into the HCI (Hue-Chroma-Intensity) colour space and then local thresholding of the chroma component to extract a binary root image. Possible chromatic discolourations, different from background colour, are added to the roots from blue or red chroma subcomponent images after thresholding. At the second stage, dark discolourations are extracted by local fuzzy c-means clustering of an HCI intensity image within the binary root mask. Fuzzy clustering is applied in local windows around the series of sample points on roots medial axes (skeleton). The performance of the proposed method is compared with hand-labelled segmentation for a series of several root systems.

DOI: https://doi.org/10.2478/v10006-009-0055-x | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 679 - 689
Published on: Dec 31, 2009
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2009 Jarosław Gocławski, Joanna Sekulska-Nalewajko, Ewa Gajewska, Marzena Wielanek, published by University of Zielona Góra
This work is licensed under the Creative Commons License.

Volume 19 (2009): Issue 4 (December 2009)