Segmentation of X-ray tomography images of compacted soils

被引:9
|
作者
Ramesh, Sabari [1 ]
Thyagaraj, T. [1 ]
机构
[1] Indian Inst Technol Madras, Dept Civil Engn, Chennai 600036, Tamil Nadu, India
关键词
Thresholding; Compacted soils; X-ray tomography; Mercury intrusion porosimetry; Image segmentation; Clay-sand mixtures; COMPUTED-TOMOGRAPHY; CLAY; MICROSTRUCTURE; BENTONITE; BEHAVIOR; QUANTIFICATION; EVOLUTION; CT; MICROTOMOGRAPHY; RECONSTRUCTION;
D O I
10.1007/s40948-021-00322-w
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
X-ray computed tomography (X-ray CT) in tandem with mercury intrusion porosimetry (MIP) has gained importance among researchers for examining the internal structure of geomaterials owing to the wide scale of coverage. The success of the X-ray CT lies in the proper segmentation of the acquired images during image processing. This study proposes a novel methodology for finding out the most probable threshold number for the segmentation of X-ray CT images of compacted soils as well as the quantification of small and large pores beyond the detection range of the MIP test. The methodology was developed based on total void ratio, tomographic void ratio and total cumulative mercury intruded void ratio obtained from vernier caliper measurements, analysis of X-ray CT images and MIP data of compacted soil specimen, respectively. The threshold number obtained was evaluated by visual observations of X-ray CT images and their corresponding binary images. The evaluation results showed that the threshold number obtained from the proposed methodology could precisely separate the soil particles from the voids in X-ray CT images and also gave a complete range of different pore sizes in the compacted soil specimen. Thus this research finds its significance in different image segmentation applications in the areas of geotechnical and geoenvironmental engineering. Also, the study on the variation of threshold number with different parameters showed that the threshold number is directly proportional to the compaction energy and sand content whereas it is inversely related to the size of the specimen.
引用
收藏
页数:18
相关论文
共 50 条
  • [31] Use of X-ray tomography for examining root architecture in soils
    Hou, Lei
    Gao, Wei
    der Bom van, Frederik
    Weng, Zhe
    Doolette, Casey L.
    Maksimenko, Anton
    Hausermann, Daniel
    Zheng, Yunyun
    Tang, Caixian
    Lombi, Enzo
    Kopittke, Peter M.
    GEODERMA, 2022, 405
  • [32] Improve the Detection and Segmentation of Lung Nodule X-ray Images
    Saad, Elhusain
    2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2022 - Proceeding, 2022, : 499 - 504
  • [33] Image segmentation optimisation for X-ray images of airline luggage
    Singh, M
    Singh, S
    CIHSPS 2004: PROCEEDINGS OF THE 2004 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR HOMELAND SECURITY AND PERSONAL SAFETY, 2004, : 10 - 17
  • [34] Deep learning based guidewire segmentation in x-ray images
    Wagner, Martin G.
    Laeseke, Paul
    Speidel, Michael A.
    MEDICAL IMAGING 2019: PHYSICS OF MEDICAL IMAGING, 2019, 10948
  • [35] A New Algorithm for Segmentation and Fracture Detection in X-Ray Images
    Bulut, Sabri
    Ozcinar, Alican
    Ciftcioglu, Caglar
    Akpek, Ali
    2015 MEDICAL TECHNOLOGIES NATIONAL CONFERENCE (TIPTEKNO), 2015,
  • [36] A Cumulative Sums Algorithm for Segmentation of Digital X-ray Images
    Vorobeychikov, S. E.
    Chakhlov, S. V.
    Udod, V. A.
    JOURNAL OF NONDESTRUCTIVE EVALUATION, 2019, 38 (03)
  • [37] Segmentation on the Dental Periapical X-Ray Images for Osteoporosis Screening
    Sela, Enny Itje
    Hartati, Sri
    Harjoko, Agus
    Wardoyo, Retantyo
    Munakhir, M. S.
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2013, 4 (07) : 147 - 151
  • [38] Segmentation and Classification of Total Hip Endoprosthesis in X-Ray Images
    Buechner, Hannah
    Malik, Maximilian
    Baumgartner, Heiko
    Springer, Fabian
    Laux, Florian
    Burgert, Oliver
    MEDICAL IMAGING 2022: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING, 2022, 12034
  • [39] Deep instance segmentation of teeth in panoramic X-ray images
    Jader, Gil
    Fontinele, Jefferson
    Ruiz, Marco
    Abdalla, Kalyf
    Pithon, Matheus
    Oliveira, Luciano
    PROCEEDINGS 2018 31ST SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), 2018, : 400 - 407
  • [40] A Cumulative Sums Algorithm for Segmentation of Digital X-ray Images
    S. E. Vorobeychikov
    S. V. Chakhlov
    V. A. Udod
    Journal of Nondestructive Evaluation, 2019, 38