Journal of the Society of Materials Science, Japan
Online ISSN : 1880-7488
Print ISSN : 0514-5163
ISSN-L : 0514-5163
Technical Topic
Application of Computer Vision to Fractography
Miho Muramatsu, Zhi-Lei Wang, Toshio Ogawa, Yoshitaka Adachi, Kyohei Ishikawa, Hiroyuki Shirahata, Masaaki Fujioka
Author information
Keywords: Deep learning, Computer vision, Fractography, Morphology, Segmentation, Hough transform
JOURNAL FREE ACCESS

2020 Volume 69 Issue 9 Pages 640-643

Details
Download PDF (1470K)
Download citation RIS

(compatible with EndNote, Reference Manager, ProCite, RefWorks)

BIB TEX

(compatible with BibDesk, LaTeX)

Text
How to download citation
Contact us
Abstract

This study focusses on computer vision to be applied to fractography. Automatic image segmentation by Hough transform and average brightness in region of interest was performed to find an origin of brittle fracture in martensitic steels. In addition, it is emphasized that morphology of microstructure or fracture surface should be quantified as much as possible to extract its features.

Content from these authors
© 2020 by The Society of Materials Science, Japan
Previous article Next article
Favorites & Alerts

Recently viewed articles
Predecessor

journal of the Japan Society for Testing Materials

Share this page
feedback
 Top