Defect detection, which plays a positive role in reducing or avoiding accidents, is the key to ensuring the operational safety of trains. In this paper, a combining computed framework is designed for defect detection in digital radiography (DR) images of castings on a railway freight car, combining the two classical geometry active contour models: CV and LBF. Firstly, the LBF model is used to extract workpiece regions including defects, so that the strong edge effect can be eliminated on detection. Secondly, after enhancing the local workpiece image contrast, the CV model is chosen to segment the defect regions. Finally, after removing pseudo-defects by setting a threshold, the geometric parameters such as centroid and area of defect regions are obtained. The experimental results demonstrate that this combining method can accurately segment defect regions in the DR image and extract useful information of geometric parameters.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Defect segmentation in digital radiography images of castings on a railway freight car


    Additional title:

    Fehlersegmentierung in digitalen radiographischen Bildern von Gussteilen eines Güterwagens


    Contributors:
    Liu, Linghui (author) / Li, Zeng (author)

    Published in:

    Insight ; 53 , 7 ; 372-376


    Publication date :

    2011


    Size :

    5 Seiten, 6 Bilder, 2 Tabellen, 15 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




    Validation of digital radiography for castings

    Emerald Group Publishing | 2007


    Defects Detection for Casting of Railway Freight Car Using X-Ray Radiography

    Zou, Yong Ning ;Li, Jian Wei ;Wang, Jue | Trans Tech Publications | 2011



    Railway freight car bogie and railway freight car

    XU SHANCHAO / XING SHUMING / LIU ZHENMING et al. | European Patent Office | 2015

    Free access

    Railway freight carriage

    GAO WEI / YE QINGLONG / WU XIANGNAN | European Patent Office | 2020

    Free access