Train front foreign matter invasion detection method and system based on image processing

Abstract

The invention provides a train front foreign matter intrusion detection method and system based on image processing, and the method comprises the following steps: collecting a monitoring video of a track in front of a train in a running process of the train, and dividing the monitoring video into a plurality of monitoring images; establishing a dangerous area foreign matter detection window in themonitoring image, and extracting a rail dangerous area detection image, located in the dangerous area foreign matter detection window, of the monitoring image; preprocessing the track dangerous areadetection image; extracting a contour feature detection image of the preprocessed track dangerous area detection image by adopting an edge extraction algorithm; calculating a similarity value betweenthe contour feature detection image and a pre-established foreign-matter-free reference image; and comparing the calculated similarity value with a preset threshold value, and judging whether foreignmatters exist or not. According to the invention, automatic detection of foreign matters in front of the train is realized, the detection precision is high, manpower and cost are saved, and traffic accidents in the train operation process are effectively avoided.

Description

technical field [0001] The present application relates to the technical field of foreign object intrusion detection in front of a train, in particular to a method and system for detecting foreign object intrusion in front of a train based on image processing. Background technique [0002] my country's high-speed railways are distributed in a wide area, long distances, complex geological conditions, and severe natural disasters. At the same time, expressways are characterized by day and night operations, closed types, and only trains are allowed. Due to the characteristics of long distance, wide distribution area, day and night operation, and closed type, when natural disasters such as landslides and geological subsidence occur along the high-speed railway, road traffic failure warnings cannot be issued in time, which is likely to cause serious traffic safety accidents and chain reactions. In order to reduce high-speed railway traffic accidents, reduce casualties and property...

AI Technical Summary

Problems solved by technology

[0003] Rolling stones, pedestrians or animals and other foreign objects invade the railway boundary, which is sudden, irregular and unpredictable, frequently causing railway traffic accidents and seriously threatening the safety of people's lives. Traditional track detection mainly relies on manpower. Setting up a large number of inspectors to check the intrusion of the track, but it consumes manpower and financial resources, and the response to emergency accidents is not fast enough

[0004] In addition, the video surveillance system is used for railway safety monitoring to monitor whether there are foreign objects intruding into the railway boundary. However, the current video surveillance system requires special personnel to monitor, and the workload of the monitoring personnel is heavy. When they are tired, omissions are prone to occur, causing danger. Hidden danger

The existing method of using a laser curtain wall for foreign object monitoring, this method detects intruding foreign objects by installing multiple two-dimensional laser sensors to form a laser curtain wall, this method has a fast detection speed and high sensitivity, but the installation is relatively complicated and is greatly affected by the environment. Only a few sections can be detected, the size and shape of the foreign matter cannot be accurately measured, and the cost is high

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