Multi-channel image fusion in ultraviolet dynamic detection on electric railways

Yan-guo Wang; Jun Fang; Liusheng Qi; Dapeng Xie; Liandong Li; Zichen Gu; Guoyue Liu; Kai Tao; Liang Sheng

doi:10.1117/12.2623389

16 February 2022 Multi-channel image fusion in ultraviolet dynamic detection on electric railways

Yan-guo Wang, Jun Fang, Liusheng Qi, Dapeng Xie, Liandong Li, Zichen Gu, Guoyue Liu, Kai Tao, Liang Sheng

Proceedings Volume 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021); 120830Y (2022) https://doi.org/10.1117/12.2623389
Event: Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 2021, Kunming, China

Abstract

Catenary is an important infrastructure along electric railways, which should be periodically checked to guarantee the normal working status of power supply for the trains. Technologies of ultraviolet detection has been introduced into catenary inspection, and it can be used to detect the electrical state for insulators that are the isolation components between high voltage and low voltage in catenary. However, due to the dynamic detection condition with the running of catenary inspection car, the performance of multi-channel image fusion becomes a key issue in the application on electric railways. In this paper, we proposed a multi-channel image fusion method for the ultraviolet and visible image in dynamic detection on electric railways. The ultraviolet detection module is designed with dual optical coupling alignment, which guarantees the consistency of multi-channel in spatial domain. The post detection is adopted and used as an external trigger signal for both the ultraviolet and visible cameras, which are working in triggered acquisition mode with good time synchronization. Finally, insulator localization algorithms based on deep learning are utilized in the automatic detection of insulator area in visible image, and the ultraviolet signals are successfully extracted from the image fusion results. The performance of multi-channel image fusion method proposed in the paper has been validated, in both lab test and dynamic test on electric railways

Citation Download Citation

Yan-guo Wang, Jun Fang, Liusheng Qi, Dapeng Xie, Liandong Li, Zichen Gu, Guoyue Liu, Kai Tao, and Liang Sheng "Multi-channel image fusion in ultraviolet dynamic detection on electric railways", Proc. SPIE 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 120830Y (16 February 2022); https://doi.org/10.1117/12.2623389

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KEYWORDS

Ultraviolet radiation

Image fusion

Visible radiation

Ultraviolet detectors

Cameras

Inspection

Signal detection

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