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Importance of automatic threshold for image segmentation for accurate measurement of fine roots of woody plants / Význam automatického prahovania na obrazovú segmentáciu pre presné merania jemných koreňov drevín Cover

Importance of automatic threshold for image segmentation for accurate measurement of fine roots of woody plants / Význam automatického prahovania na obrazovú segmentáciu pre presné merania jemných koreňov drevín

Open Access
|Mar 2015

Abstract

The fine roots are considered the key organs for plant survival, growth and productivity. Measurement of fine roots variables is easily and conveniently achieved by means of digital image. The descriptive variables like root area, surface, total length and diameter distribution may be obtained from the image. Analysis of digital image consists from several steps, each of them represents potential source of the error. In this article we want to evaluate the automatic thresholding and its impact on principal variables obtainable from digital scans of the fine roots. We compare 16 different thresholding methods and compare them with the human processed binary images of roots of cork oak (Quercus suber L.). We found some of the thresholding methods perform significantly better than others in the estimation of total projected area however the length estimation error points out a little different order of accuracy

DOI: https://doi.org/10.1515/forj-2015-0007 | Journal eISSN: 2454-0358 | Journal ISSN: 2454-034X
Language: English
Page range: 244 - 249
Published on: Mar 4, 2015
Published by: National Forest Centre and Czech University of Life Sciences in Prague, Faculty of Forestry and Wood Sciences
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2015 Peter Surový, Cati Dinis, Róbert Marušák, Nuno de Almeida Ribeiro, published by National Forest Centre and Czech University of Life Sciences in Prague, Faculty of Forestry and Wood Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.