A Uniform Illumination Model of Rail Surface Suitable for Machine Vision Inspection

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

In the process of rail surface defect detection, the collected image data is the original data, which is the basis of the whole system. Their quality determines the accuracy of later defect extraction and the speed of the algorithm. In order to collect high-quality rail surface images, this paper proposes an optical theoretical model for rail surface defect detection that can provide stable and uniform illumination conditions, analyses the relationship between image histogram and image quality, and studies a reflective surface that can avoid. The light source directly illuminates the surface of the rail. By designing a reasonable lighting system, 270-degree stable and uniform lighting is provided for the rail surface. Experiments demonstrate the rationality of the proposed model. The results show that the stable uniform illumination enhances the contrast of defects and background, which facilitates image recognition in post-image processing. Moreover, the incident angle of the uniform illumination is evenly distributed, which effectively eliminates the image quality influence caused by vibration and other reasons during the detection process.

Details

Original languageEnglish
Title of host publicationDevelopments and Applications in SmartRail, Traffic, and Transportation Engineering
EditorsLimin Jia, Yong Qin, Said Easa
PublisherSpringer Science and Business Media B.V.
Pages547-553
Number of pages7
ISBN (electronic)978-981-97-3682-9
ISBN (print)978-981-97-3681-2, 978-981-97-3684-3
Publication statusPublished - 2024
Peer-reviewedYes

Publication series

SeriesLecture Notes in Electrical Engineering
Volume1209 LNEE
ISSN1876-1100

Conference

Title7th International Conference on SmartRail, Traffic, and Transportation Engineering
Abbreviated titleICSTTE 2023
Conference number7
Duration28 - 30 July 2023
Website
CityChangsha
CountryChina

Keywords

Keywords

  • Defect, Detect, Machine Vision, Rail Surface, Uniform Illumination