Visual analysis based mountain railway side slope rockfall detecting method

A visual analysis and detection method technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as falling in the rail area, and achieve the effect of improving accuracy, low cost, and wide detection range

Inactive Publication Date: 2016-07-27
李云栋 +1
View PDF3 Cites 29 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The method of protective net + sensor also has many limitations, because falling rocks may fly over the protective net and fall directly into the rail area

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Visual analysis based mountain railway side slope rockfall detecting method
  • Visual analysis based mountain railway side slope rockfall detecting method
  • Visual analysis based mountain railway side slope rockfall detecting method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0046] The method based on video analysis adopted in the embodiment of the present invention does not analyze the trajectory of falling rocks, but adopts methods of object segmentation and object classification. Firstly, the track area is identified, and then the image in the track area is segmented to detect the foreground target. Finally, the target is classified by deep learning, and the interfering target is eliminated. The method of the embodiment of the present invention has the advantages of wide detection range and low cost of the video analysis method, and improves detection accuracy at the same time.

[0047] The processing flow of a method for detecting rockfall on mountainous railway slopes based on visual analysis proposed by the embodiment of the present invention is as follows: figure 1 As shown, the following processing steps are included:

[0048] Step S110, read the image.

[0049] A Gigabit network digital camera is used to collect images of mountain railw...

Embodiment 2

[0070] This embodiment provides a kind of mountainous railway slope rockfall detection device based on vision analysis, the structure of this device is as follows image 3 As shown, the following modules are included:

[0071] Image collection module 31, for collecting the image of mountain railway;

[0072] The image acquisition module 32 of the railroad track area is used to carry out local linear detection and Hough transform to the image of the mountainous railway to obtain the image of the railroad track area;

[0073] The foreground target image acquisition module 33 is used to perform differential processing and binarization segmentation processing on the image of the railroad track area to obtain the foreground target image;

[0074] The rockfall target image acquisition module 34 is used to construct a classifier based on the trained deep network, input the foreground target image into the classifier, and judge whether the foreground target image belongs to a target co...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

An embodiment of the invention provides a visual analysis based mountain railway side slope rockfall detecting method. The method mainly comprises collecting an image of a mountain railway, performing local linear detection and Hough exchange on the image and obtaining an image of a railway area; performing differential treatment and binaryzation segmentation process on the image of the railway image and obtaining a foreground target image; constructing a classifier based on a well-trained deep network and inputting the foreground target image into the classifier and judging whether the foreground target image belongs to the target image containing rockfall or not according to an output result of the classifier. According to the embodiment of the invention, the railway area is identified at first, then the image in the railway area is segmented, the foreground target is detected, and finally the target is classified through deep learning and interference targets are removed. The scheme provided by the embodiment of the invention has advantages of wide detection range, low cost and the like of a video analysis method. At the same time, the rockfall image detection accuracy is improved.

Description

technical field [0001] The invention relates to the field of railway foreign matter invasion and limitation, in particular to a method for detecting rockfall on mountainous railway slopes based on visual analysis. Background technique [0002] In mountainous road sections where geological disasters occur frequently, rockfall from slopes often invades the railway boundary, which seriously endangers the safe operation of trains. Rockfall on slopes is characterized by suddenness, irregularity, and unpredictability. If the driver only relies on the driver to visually detect foreign objects and then take braking measures during the operation of the train, accidents will not be effectively avoided, and traffic safety will be seriously threatened. [0003] Intrusion of foreign objects including rockfall on slopes poses a serious threat to the safe operation of railways. Scholars at home and abroad have gradually realized the importance of intrusion detection and carried out related...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06T2207/20081G06T2207/30184
Inventor 李云栋赵维刚
Owner 李云栋
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap