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

Na Geng; Hu Sheng; Weizhi Sun; Yifeng Wang; Tan Yu; Zihan Liu

doi:10.1117/12.3014444

9 January 2024 Image segmentation of rail surface defects based on fractional order particle swarm optimization 2D-Otsu algorithm

Na Geng, Hu Sheng, Weizhi Sun, Yifeng Wang, Tan Yu, Zihan Liu

Author Affiliations +

Proceedings Volume 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023); 129690A (2024) https://doi.org/10.1117/12.3014444
Event: International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023), 2023, Qingdao, China

Abstract

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.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Na Geng, Hu Sheng, Weizhi Sun, Yifeng Wang, Tan Yu, and Zihan Liu "Image segmentation of rail surface defects based on fractional order particle swarm optimization 2D-Otsu algorithm", Proc. SPIE 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023), 129690A (9 January 2024); https://doi.org/10.1117/12.3014444

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available