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Yue, B., Wang, Y., Min, Y., Zhang, Z., Wang, W. and Yong, J. (2019) Rail Surface Defect Recognition Method Based on Adaboost Multi-Classifier Combination. 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Lanzhou, 18-21 November 2019, 391-396.
https://doi.org/10.1109/apsipaasc47483.2019.9023096

has been cited by the following article:

• TITLE: Research on Image Preprocessing Algorithm for Rail Surface Recognition

  AUTHORS: Jihong Zuo, Lili Liu, Chuanyin Yang, Yufeng Tang

  KEYWORDS: Image Processing, Image Graying, Image Denoising, Image Database

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.14 No.10, October 23, 2024

  ABSTRACT: The rail surface status image is affected by the noise in the shooting environment and contains a large amount of interference information, which increases the difficulty of rail surface status identification. In order to solve this problem, a preprocessing method for the rail surface state image is proposed. The preprocessing process mainly includes image graying, image denoising, image geometric correction, image extraction, data amplification, and finally building the rail surface image database. The experimental results show that this method can efficiently complete image processing, facilitate feature extraction of rail surface status images, and improve rail surface status recognition accuracy.