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Titel: Segmentation of Lath-Like Structures via Localized Identification of Directionality in a Complex-Phase Steel
VerfasserIn: Müller, Martin
Stanke, Gerd
Sonntag, Ulrich
Britz, Dominik
Mücklich, Frank
Sprache: Englisch
Titel: Metallography, Microstructure, and Analysis
Bandnummer: 9
Heft: 5
Seiten: 709–720
Verlag/Plattform: Springer Nature
Erscheinungsjahr: 2020
Freie Schlagwörter: Microstructure
Segmentation
Local orientation and direction analysis
Region growing
Steel
Bainite
DDC-Sachgruppe: 600 Technik
Dokumenttyp: Journalartikel / Zeitschriftenartikel
Abstract: In this work, a segmentation approach based on analyzing local orientations and directions in an image, in order to distinguish lath-like from granular structures, is presented. It is based on common image processing operations. A window of appropriate size slides over the image, and the gradient direction and its magnitude inside this window are determined for each pixel. The histogram of all possible directions yields the main direction and its directionality. These two parameters enable the extraction of window positions which represent lath-like structures, and procedures to join these positions are developed. The usability of this approach is demonstrated by distinguishing lath-like bainite from granular bainite in so-called complex-phase steels, a segmentation task for which automated procedures are not yet reported. The segmentation results are in accordance with the regions recognized by human experts. The approach’s main advantages are its use on small sets of images, the easy access to the segmentation process and therefore a targeted adjustment of parameters to achieve the best possible segmentation result. Thus, it is distinct from segmentation using deep learning which is becoming more and more popular and is a promising solution for complex segmentation tasks, but requires large image sets for training and is difficult to interpret.
DOI der Erstveröffentlichung: 10.1007/s13632-020-00676-9
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-337325
hdl:20.500.11880/31067
http://dx.doi.org/10.22028/D291-33732
ISSN: 2192-9270
2192-9262
Datum des Eintrags: 6-Apr-2021
Fakultät: NT - Naturwissenschaftlich- Technische Fakultät
Fachrichtung: NT - Materialwissenschaft und Werkstofftechnik
Professur: NT - Prof. Dr. Frank Mücklich
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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