Under the influence of high density operation and natural environment, the rail surface will appear abrasion damage, which will affect the safety and comfort of the train. Rail surface defect detection is an important part to ensure the safe and efficient operation of railway system. In order to distinguish whether there are defects on the rail surface, a method of rail surface defect image segmentation based on FPSO 2D-Otsu algorithm is proposed. The rail image is denoised and enhanced by adaptive fractional calculus, and then the rail image is segmented by FPSO 2D-Otsu algorithm. In order to verify the accuracy of the algorithm, the proposed algorithm is compared with PSO 2D-Otsu image segmentation algorithm. The experimental results show that the accuracy of FPSO 2D-Otsu algorithm in rail image segmentation is improved from 48.76% to 83.59% compared with PSO 2D-Otsu algorithm.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Image segmentation of rail surface defects based on fractional order particle swarm optimization 2D-Otsu algorithm


    Contributors:
    Zhou, Huiyu (editor) / Yang, Qinmin (editor) / Geng, Na (author) / Sheng, Hu (author) / Sun, Weizhi (author) / Wang, Yifeng (author) / Yu, Tan (author) / Liu, Zihan (author)

    Conference:

    International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023) ; 2023 ; Qingdao, China


    Published in:

    Proc. SPIE ; 12969


    Publication date :

    2024-01-09





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





    An Improved Otsu Image Segmentation Algorithm for Path Mark Detection under Variable Illumination

    Jin, L.-s. / Tian, L. / Wang, R.-b. et al. | British Library Conference Proceedings | 2005



    Hybrid particle swarm optimisation algorithm for image segmentation

    Zhang,J. / Lu,J. / Li,H. et al. | Automotive engineering | 2012