Rail transit obstacle recognition technology based on infrared image and SURF algorithm

Bo Liu; Yu Zhang; Cheng Li

doi:10.1117/12.3009224

11 October 2023 Rail transit obstacle recognition technology based on infrared image and SURF algorithm

Bo Liu, Yu Zhang, Cheng Li

Proceedings Volume 12918, Fourth International Conference on Computer Science and Communication Technology (ICCSCT 2023); 129180P (2023) https://doi.org/10.1117/12.3009224
Event: International Conference on Computer Science and Communication Technology (ICCSCT 2023), 2023, Wuhan, China

Abstract

Currently, rail transit has developed more and more intelligently, and intelligent vehicles are of significance in reducing traffic accidents and improving transportation capacity and have broad market prospects. This research combines infrared image acquisition and machine algorithms for obstacle recognition. The SURF algorithm performs feature extraction and description, and elimination of mismatched point pairs on infrared and visible light images, which can do image recognition on track obstacles. On this basis, a foreign object monitoring system consisting of an optical imaging subsystem, a lighting and detection light source subsystem, a pan tilt synchronous control subsystem, an image acquisition and processing subsystem, and an installation fixture and protection subsystem was designed. Finally, a demonstration application of foreign object monitoring under different working conditions in the section adjacent to the elevated line and highway of Guangzhou Metro Line 4, the open line section (K46+175) from Tung Chung Station to Huangge Auto Town station, for the 100 m section of the uplink and downlink double lines was carried out on the proposed system, which verified that the foreign object detection rate was 100% based on the test data, and the maximum detection response time was 4s (less than 5s). The relative deviations between the detected foreign objects and actual positions were less than 2.13% and the relative deviations between the detected foreign objects sizes and the actual sizes were less than 8.8%, which fully proved the effectiveness of the monitoring system.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bo Liu, Yu Zhang, and Cheng Li "Rail transit obstacle recognition technology based on infrared image and SURF algorithm", Proc. SPIE 12918, Fourth International Conference on Computer Science and Communication Technology (ICCSCT 2023), 129180P (11 October 2023); https://doi.org/10.1117/12.3009224

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Infrared imaging

Infrared radiation

Visible radiation

Detection and tracking algorithms

Object detection

Image registration

Radar

Show All Keywords

Keywords/Phrases

Search In:

Publication Years