Open AccessResearch on 3D crack segmentation of CT images of oil rock core
Author(s) -
Yongning Zou,
Gongjie Yao,
Jue Wang
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0258463
Subject(s) - image segmentation , segmentation , artificial intelligence , core (optical fiber) , geology , binary image , image (mathematics) , pattern recognition (psychology) , computer vision , computer science , gray level , scale space segmentation , image processing , telecommunications
In this paper, we propose a framework for CT image segmentation of oil rock core. According to the characteristics of CT image of oil rock core, the existing level set segmentation algorithm is improved. Firstly, an algorithm of Chan-Vese (C-V) model is carried out to segment rock core from image background. Secondly the gray level of image background region is replaced by the average gray level of rock core, so that image background does not affect the binary segmentation. Next, median filtering processing is carried out. Finally, an algorithm of local binary fitting (LBF) model is executed to obtain the crack region. The proposed algorithm has been applied to oil rock core CT images with promising results.