Conference paper

MUSIL Marek. Effectiveness of Approaches for Rail Candidates Detection and Verification of the SVM. In: ICTIC - Proceedings in Conference of Informatics and Management Sciences. Žilina: University of Žilina, 2016, pp. 152-156. ISBN 978-80-554-1196-5. Available from: http://www.ictic.sk/archive/?vid=1&aid=2&kid=50501-285
Publication language:english
Original title:Effectiveness of Approaches for Rail Candidates Detection and Verification of the SVM
Title (cs):Účinnost přístupu detekce kandidátů na kolejnice a ověření SVM
Pages:152-156
Proceedings:ICTIC - Proceedings in Conference of Informatics and Management Sciences
Conference:ICTIC 2016, an International Virtual Conference
Series:Volume 5 Issue 1
Place:Žilina, SK
Year:2016
URL:http://www.ictic.sk/archive/?vid=1&aid=2&kid=50501-285
ISBN:978-80-554-1196-5
DOI:10.18638/ictic.2016.5.1
Publisher:University of Žilina
Keywords
rails detection,computer vision,Histogram of Oriented Gradients,pixel-per-pixel method,Support Vector Machine

Annotation
Rail candidates detection is the primary task in railway recognition systems based on recognition in images taken from the camera mounted on the board of the locomotive. In order to reduce the classifier complexity, effective and responsible rail candidates generation plays an important role without placing big decision responsibility on a further classifier stage. There are two basic options. Due to the rich complex environment along the track, pixel-per-pixel methods are often omitted. The second option involving a thorough investigation around a pixel is preferred. In this paper, we present comparison between two different approaches to rail candidates detection, each representing one of the basic groups, furthermore consequences in rail hypotheses generation. We introduce the finding that using the SVM is more efficient than the method based on pixel-per-pixel.
BibTeX:
@INPROCEEDINGS{
   author = {Marek Musil},
   title = {Effectiveness of Approaches for Rail Candidates
	Detection and Verification of the SVM},
   pages = {152--156},
   booktitle = {ICTIC - Proceedings in Conference of Informatics and
	Management Sciences},
   series = {Volume 5 Issue 1},
   year = {2016},
   location = {{\v{Z}}ilina, SK},
   publisher = {University of {\v{Z}}ilina},
   ISBN = {978-80-554-1196-5},
   doi = {10.18638/ictic.2016.5.1},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=11174}
}

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