Importance of automatic threshold for image segmentation for accurate measurement of fine roots of woody plants

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F14%3A66746" target="_blank" >RIV/60460709:41320/14:66746 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.nlcsk.sk/fj/images/pdf/Rocnik_60/Cislo_4_2014/Surovy_akol.pdf" target="_blank" >http://www.nlcsk.sk/fj/images/pdf/Rocnik_60/Cislo_4_2014/Surovy_akol.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Importance of automatic threshold for image segmentation for accurate measurement of fine roots of woody plants

Popis výsledku v původním jazyce

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 performsignificantly better than others in the estimation of total projected area however the length estimation error points out a little different order of accuracy.

Název v anglickém jazyce

Importance of automatic threshold for image segmentation for accurate measurement of fine roots of woody plants

Popis výsledku anglicky

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 performsignificantly better than others in the estimation of total projected area however the length estimation error points out a little different order of accuracy.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

GK - Lesnictví

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Lesnicky časopis (Forestry Journal)

ISSN

0323-1046

e-ISSN

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Svazek periodika

60

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

SK - Slovenská republika

Počet stran výsledku

6

Strana od-do

244-249

Kód UT WoS článku

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EID výsledku v databázi Scopus

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