Railway foreign matter invasion detection method based on railway monitoring

Abstract

The invention provides a railway foreign matter invasion detection method based on railway monitoring. The method comprises the following steps: training YOLOv3 by utilizing an original image containing foreign matter invasion of a monitoring video in a known railway scene; obtaining a trained model weight; acquiring a monitoring video of a railway scene to be monitored, extracting a series of to-be-monitored original images from a monitoring video, processing the to-be-monitored original images through an existing Gaussian mixture model, and sequentially performing morphological processing, threshold adaptation and non-maximum suppression algorithm processing on output binary images to obtain an image area containing foreign matter invasion; and inputting the image area containing foreignmatter invasion into the YOLOv3, wherein the YOLOv3 outputs the foreign matter type and the foreign matter positioning position information in the corresponding original image according to the trained model weight. According to the method, the false alarm rate caused by the Gaussian mixture algorithm is reduced, the detection effect of the YOLOv3 algorithm on a long-distance target or/and a smalltarget is improved, and railway foreign matter invasion can be effectively monitored.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for detecting railway foreign object intrusion based on railway monitoring. Background technique [0002] As of the end of 2018, China's railway operating mileage reached 131,000 kilometers, including 29,000 kilometers of high-speed rail. With the large-scale speed-up of railways, the security problems of railway perimeters have become increasingly prominent. The invasion of foreign objects at the railway perimeter will cause large-scale delays in railway transportation, and even cause heavy casualties and economic losses. Sabotage activities against railways and related facilities occur from time to time, which brings serious hidden dangers and threats to railway operation safety. The safety of railway perimeters has become the top priority of railway safety management. At present, the railway management department has adopted a variety of technical defense m...

AI Technical Summary

Problems solved by technology

The advantage of the target detection algorithm based on deep learning lies in high detection accuracy and low false alarm rate, but the d

Images