Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 7-Day Trial for You or Your Team.

Learn More →

A Refined Global Segmentation of X-Ray CT Images for Multi-phase Geomaterials

A Refined Global Segmentation of X-Ray CT Images for Multi-phase Geomaterials X-ray computed tomography images of three-phase silica sand and glass bead specimens are analyzed and used to evaluate the segmentation performances of Otsu-, and recursion-based multilevel algorithms. A global image segmentation technique that combines iterative and recursive algorithms, namely a refined statistics-based global segmentation is proposed for segmenting multi-phase granular geomaterials. The performance of the proposed algorithm is tested by segmenting partially saturated silica sand and glass bead specimens. For the tested silica sand specimen, the refined statistics method estimated void ratio and degree of saturation were 0.67 and 39.35%. The estimates for the glass bead specimen yielded 0.64 and 43.49%, respectively. The true void ratio (0.66) and degree of saturation (37.71%) were determined with a user-controlled Image processing software package—Image-Pro. It was found that the proposed method estimated the void ratio and the degree of saturation with 1.52 and 4.35 percent errors for the silica sand and with 15.63 and 0.34 percent errors for the glass bead, respectively. The computational time of the proposed method was found to be shorter than other methods considered. Overall, it is concluded that the proposed technique performed better in segmenting three-phase granular geomaterials. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Nondestructive Evaluation Springer Journals

A Refined Global Segmentation of X-Ray CT Images for Multi-phase Geomaterials

Download PDF
12 pages

Loading next page...
 
/lp/springer-journals/a-refined-global-segmentation-of-x-ray-ct-images-for-multi-phase-qhKc00fx4J

References (59)

Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Engineering; Structural Mechanics; Characterization and Evaluation of Materials; Vibration, Dynamical Systems, Control; Classical Mechanics
ISSN
0195-9298
eISSN
1573-4862
DOI
10.1007/s10921-018-0508-y
Publisher site
See Article on Publisher Site

Abstract

X-ray computed tomography images of three-phase silica sand and glass bead specimens are analyzed and used to evaluate the segmentation performances of Otsu-, and recursion-based multilevel algorithms. A global image segmentation technique that combines iterative and recursive algorithms, namely a refined statistics-based global segmentation is proposed for segmenting multi-phase granular geomaterials. The performance of the proposed algorithm is tested by segmenting partially saturated silica sand and glass bead specimens. For the tested silica sand specimen, the refined statistics method estimated void ratio and degree of saturation were 0.67 and 39.35%. The estimates for the glass bead specimen yielded 0.64 and 43.49%, respectively. The true void ratio (0.66) and degree of saturation (37.71%) were determined with a user-controlled Image processing software package—Image-Pro. It was found that the proposed method estimated the void ratio and the degree of saturation with 1.52 and 4.35 percent errors for the silica sand and with 15.63 and 0.34 percent errors for the glass bead, respectively. The computational time of the proposed method was found to be shorter than other methods considered. Overall, it is concluded that the proposed technique performed better in segmenting three-phase granular geomaterials.

Journal

Journal of Nondestructive Evaluation – Springer Journals

Published: Jul 10, 2018

There are no references for this article.