Accessible Unlicensed Requires Authentication Published by De Gruyter August 14, 2021

Image Processing using Open Source Tools and their Implementation in the Analysis of Complex Microstructures

Bildverarbeitung mithilfe von Open-Source-Tools und deren Anwendung bei der Analyse komplexer Gefüge
U. P. Nayak, M. Müller, D. Britz, M.A. Guitar and F. Mücklich
From the journal Practical Metallography

Abstract

Considering the dependance of materials’ properties on the microstructure, it is imperative to carry out a thorough microstructural characterization and analysis to bolster its development. This article is aimed to inform the users about the implementation of FIJI, an open source image processing software for image segmentation and quantitative microstructural analysis.

The rapid advancement of computer technology in the past years has made it possible to swiftly segment and analyze hundreds of micrographs reducing hours’ worth of analysis time to a mere matter of minutes. This has led to the availability of several commercial image processing software programs primarily aimed at relatively inexperienced users. Despite the advantages like ‘one-click solutions’ offered by commercial software, the high licensing cost limits its widespread use in the metallographic community.

Open-source platforms on the other hand, are free and easily available although rudimentary knowledge of the user-interface is a pre-requisite. In particular, the software FIJI has distinguished itself as a versatile tool, since it provides suitable extensions from image processing to segmentation to quantitative stereology and is continuously developed by a large user community. This article aims to introduce the FIJI program by familiarizing the user with its graphical user-interface and providing a sequential methodology to carry out image segmentation and quantitative microstructural analysis.

Kurzfassung

Vor dem Hintergrund der Abhängigkeit von Werkstoffeigenschaften vom Gefüge ist die Durchführung einer eingehenden mikrostrukturellen Charakterisierung und Analyse für die Weiterentwicklung von Werkstoffen unerlässlich. Die vorliegende Arbeit soll Benutzer über die Anwendung von FIJI, einer Open-Source-Bildverarbeitungssoftware für Bildsegmentierung und quantitative Gefügeanalyse informieren.

Die rasanten Fortschritte in der Computertechnik der letzten Jahre haben eine schnelle Segmentierung und Analyse hunderter Mikroskopaufnahmen und eine Verkürzung der entsprechenden Analysedauer von Stunden auf wenige Minuten möglich gemacht. In der Folge konnten sich mehrere, auf relativ unerfahrene Anwender abzielende kommerzielle Bildverarbeitungsprogramme etablieren, die auf dem Markt erhältlich sind. Trotz ihrer Vorteile, beispielsweise „Ein-Klick-Lösungen“, verhindern die hohen Lizenzkosten dieser kommerziellen Programme eine verbreitete Nutzung in der Metallographie-Community.

Open-Source-Plattformen hingegen sind kostenlos und leicht verfügbar. Allerdings sind hier rudimentäre Kenntnisse der Benutzeroberfläche Voraussetzung. Insbesondere die Software FIJI hat sich als ein vielfältiges Tool ausgezeichnet: Sie stellt, von der Bildverarbeitung über die Segmentierung bis hin zur quantitativen Stereologie, geeignete Erweiterungen bereit und unterliegt einer fortwährenden Weiterentwicklung durch einen großen Anwenderkreis. In dieser Arbeit soll das FIJI-Programm vorgestellt werden. Dabei wird der Anwender mit der entsprechenden grafischen Benutzeroberfläche vertraut gemacht und eine sequentielle Vorgehensweise zur Durchführung von Bildsegmentierung und quantitativer Gefügeanalyse vermittelt.

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4 Acknowledgement

The authors wish to acknowledge the EFRE Funds of the European Commission and the State Chancellery of Saarland for support of activities within the ZuMat project. Additionally, U.P.N. is grateful to DAAD for the financial support.

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4 Danksagung

Die Autoren bedanken sich beim EFRE-Fonds der Europäischen Kommission und der Staatskanzlei des Saarlandes für die Förderung der Aktivitäten im Rahmen des ZuMat-Projekts. Darüber hinaus bedankt sich U.P.N. beim DAAD für die finanzielle Unterstützung.

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Supplementary Information (S. I.) / Weiterführende Informationen (w. I.)

1. https://www.irfanview.com

2. https://www.gimp.org

3. https://imagej.net/Welcome

4. https://imagej.net/Fiji/Downloads

5. https://imagej.net/Trainable_Weka_Segmentation

6. https://imagej.nih.gov/ij/plugins/index.html

7. https://imagej.net/MorphoLibJ

8. https://www.biovoxxel.de/development/

Received: 2021-05-01
Accepted: 2021-05-02
Published Online: 2021-08-14

© 2021 Walter de Gruyter GmbH, Berlin/Boston, Germany