NDLI: Rail and turnout detection using gradient information and template matching

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2013 IEEE International Conference on Intelligent Rail Transportation Proceedings

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Table of contents

IEEE ICIRT 2013 - Welcome message

Rail and turnout detection using gradient information and template matching

Content Provider	IEEE Xplore Digital Library
Author	Corsino Espino, J. Stanciulescu, B. Forin, P.
Copyright Year	2013
Description	Author affiliation: Robotic Center, Mines ParisTech, Paris, France (Stanciulescu, B.) \|\| SWE RC-FR IC-MOL RA R&D, SIEMENS S.A.S., Chatillon, France (Corsino Espino, J.; Forin, P.)
Abstract	This paper presents a railway track and turnout detection algorithm which is not based on an empirical threshold. The railway track extraction is based on an edge detection using the width of the rolling pads. This edge detection scheme is then used as an input to the RANSAC algorithm to determine the model of the rails. The turnout detection scheme is based on the Histogram of Oriented Gradient (HOG) and Template Matching (TM). The results show (i) reliable performance for our railway track extraction scheme and (ii) a correction rate of 97.31 percent for the turnout detection scheme using a Support Vector Machine (SVM) classifier.
Starting Page	233
Ending Page	238
File Size	1212229
Page Count	6
File Format	PDF
DOI	10.1109/ICIRT.2013.6696299
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Rails Support vector machines Correlation Image edge detection Rails detection Lighting Turnout detection Cameras Rail transportation
Content Type	Text
Resource Type	Article

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