NDLI: Road Boundary Detection in Challenging Scenarios

Content Provider	IEEE Xplore Digital Library
Author	Helala, M.A. Pu, K.Q. Qureshi, F.Z.
Copyright Year	2012
Abstract	This paper presents a new approach for automatic road detection in traffic cameras. The technique proposed here detects the dominant road boundary and estimates the vanishing point in images captured by traffic cameras under a wide range of lighting and environmental conditions, e.g., in images of unlit highways captured at night, etc. The approach starts by segmenting the traffic scene into a number of superpixel regions. The contours of these regions are used to generate a large number of edges which are organized into clusters of co-linearly similar sets using hierarchical bottom up clustering. A confidence level is assigned to each cluster using a statistical approach and the best clusters are chosen. Pairs of clusters with high confidence levels are then ranked and filtered according to image perspective and activity. The top ranked pair is selected as the road boundary. The proposed technique is tested on a real world dataset collected from the Ontario 401 traffic surveillance system. Experimental results demonstrate a distinct speedup and improvement in accuracy of the proposed technique in detecting the dominant road boundary in challenging scenarios compared to the state of the art Gabor filter based technique.
Starting Page	428
Ending Page	433
File Size	826318
Page Count	6
File Format	PDF
ISBN	9781467324991
e-ISBN	9780769547978
DOI	10.1109/AVSS.2012.61
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Roads Image edge detection Surveillance Lighting Superpixel Segmentation Cameras Hierarchical Clustering Road Boundary Detection Vehicles
Content Type	Text
Resource Type	Article

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