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Proceedings Paper

Vision based speed breaker detection for autonomous vehicle
Author(s): Arvind C.S.; Ritesh Mishra; Kumar Vishal; Venugopal Gundimeda
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Paper Abstract

In this paper, we are presenting a robust and real-time, vision-based approach to detect speed breaker in urban environments for autonomous vehicle. Our method is designed to detect the speed breaker using visual inputs obtained from a camera mounted on top of a vehicle. The method performs inverse perspective mapping to generate top view of the road and segment out region of interest based on difference of Gaussian and median filter images. Furthermore, the algorithm performs RANSAC line fitting to identify the possible speed breaker candidate region. This initial guessed region via RANSAC, is validated using support vector machine. Our algorithm can detect different categories of speed breakers on cement, asphalt and interlock roads at various conditions and have achieved a recall of ~0.98.

Paper Details

Date Published: 13 April 2018
PDF: 9 pages
Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106960E (13 April 2018); doi: 10.1117/12.2311315
Show Author Affiliations
Arvind C.S., Cognizant Technology Solutions Pvt. Ltd. (India)
Ritesh Mishra, Cognizant Technology Solutions Pvt. Ltd. (India)
Kumar Vishal, Cognizant Technology Solutions Pvt. Ltd. (India)
Venugopal Gundimeda, Cognizant Technology Solutions Pvt. Ltd. (India)


Published in SPIE Proceedings Vol. 10696:
Tenth International Conference on Machine Vision (ICMV 2017)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev; Jianhong Zhou, Editor(s)

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