DocumentCode :
1611733
Title :
Lane detection algorithm based on local feature extraction
Author :
Guorong Liu ; Shutao Li ; Weirong Liu
Author_Institution :
Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
fYear :
2013
Firstpage :
59
Lastpage :
64
Abstract :
An effective local feature extraction algorithm for lane detection is proposed in this paper. First, a lane region of interest (ROI) is determined by the location of road surface appeared in an image. Then, the light intensity and width of lane markings are taken as the local feature. A local threshold segmentation algorithm is utilized to extract lane-marking candidates followed by a morphological operation to obtain the accurate lane. An edge refining procedure is used to eliminate the interference and reduce computational cost. Finally, the lane marking is detected using Hough transform with some subsidiary conditions. With the proposed method, the lane can be accurately detected in conditions of fluctuating and poor illumination, as well as the interference from reflected light can be avoided effectively. The experimental results demonstrate the efficiency of the proposed method.
Keywords :
Hough transforms; feature extraction; image segmentation; mathematical morphology; object detection; road traffic; traffic engineering computing; Hough transform; ROI; computational cost reduction; edge refining procedure; interference elimination; lane detection algorithm; lane marking detection; lane markings width; lane region of interest; lane-marking candidates; light intensity; local feature extraction algorithm; local threshold segmentation algorithm; morphological operation; reflected light; road surface location; Image color analysis; Image edge detection; Image segmentation; Interference; Lighting; Roads; Vehicles; Hough transform; Lane detection; local threshold segmentation; morphological operation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Chinese Automation Congress (CAC), 2013
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-0332-0
Type :
conf
DOI :
10.1109/CAC.2013.6775702
Filename :
6775702
Link To Document :
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