Railway Snowfall Status Evaluation Based on Single Image

Jingfan  Yang; Yunpeng Wu; Yong Qing; Xiaoqing Chen; Limin Jia

doi:10.6180/jase.201909_22(3).0012

Railway Snowfall Status Evaluation Based on Single Image

Civil Engineering

(a) Original image, (b) Three-channel difference processing image, (c) Preliminary guiding image,

Jingfan Yang^1,2, Yunpeng Wu^1,2, Yong Qin ^1,3, Xiaoqing Cheng^1,3 and Limin Jia^1,3

¹State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, P.R. China
²School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, P.R. China
³Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing 100044, P.R. China

Received: January 17, 2019
Accepted: July 9, 2019
Publication Date: September 1, 2019

Download Citation: ||https://doi.org/10.6180/jase.201909_22(3).0012

ABSTRACT

The bad weather along the rail track has brought many inconveniences for driving, among which the snow weather in winter seriously threatens the safety of driving. However, existing image based methods are only focus on snow removal, this paper emphasize on snow detection after restore scene. The imaging model of snowflake in video is built, which takes snowflake individuals in video images along the railtrack as the research object. The improved guided filtering algorithm is applied to restore the background image, and then the enhanced background subtraction method is employed to extract the snowflake foreground, so as to realize the analysis and judgment of the snow status, which has an attractive detection effect. The comparison experiment for snow detection is carried out to demonstrate the efficiency of the proposed method, which achieves significant improvements over the state-of-the-art methods. Finally, a snow condition judgment standard based on video analysis is established, which matches different snow grades and video feature information. The operation and maintenance department can carry out the train speed limit management plan according to the standard, so as to ensure the safety of track operation in snowy days.

Keywords: Intelligent Transportation, Foreground Extraction, Background Difference Method, Snowfall Analysis, Driving Safety

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