JOURNAL ARTICLE

Pipeline image haze removal system using dark channel prior on cloud processing platform

Ce LiTan HeYingheng WangLiguo ZhangRuili LiuJing Zheng

Year: 2020 Journal:   International Journal of Computational Science and Engineering Vol: 22 (1)Pages: 84-84   Publisher: Inderscience Publishers

Abstract

Pipeline fault detection is very important application of pipeline robots for the security of underground drainage pipeline facilities. The detection performance of existing systems is closely related to the image definition in the complex pipeline environment in terms of darkness, water fog, haze, etc. In this paper, the techniques of dark channel prior and cloud processing are combined into the framework of pipeline image haze removal system. In the system, including the user management module, system sitting module, cloud-based image management module and image processing module, we transmit the image data with the secure cloud data control mechanism, and remove the haze in each image using dark channel prior. The experimental results show that the system has good effects on haze removal of pipe images, especially for the larger reflection area. The system can be applied to engineering practice. © 2020 Inderscience Enterprises Ltd.

Keywords:
Haze Cloud computing Pipeline (software) Computer science Channel (broadcasting) Computer vision Real-time computing Image processing Artificial intelligence Image (mathematics) Computer network Geography Meteorology Operating system

Metrics

5
Cited By
0.31
FWCI (Field Weighted Citation Impact)
0
Refs
0.59
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Water Quality Monitoring Technologies
Physical Sciences →  Environmental Science →  Water Science and Technology
Fire Detection and Safety Systems
Physical Sciences →  Engineering →  Safety, Risk, Reliability and Quality

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