DocumentCode :
569770
Title :
A lane boundary detection method based on high dynamic range image
Author :
Kou, Fei ; Chen, Weihai ; Wang, Jianhua ; Zhao, Zhiwen
Author_Institution :
Sch. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing, China
fYear :
2012
fDate :
25-27 July 2012
Firstpage :
21
Lastpage :
25
Abstract :
Every year many vehicle departure accidents happen due to the driver´s carelessness. Lane Departure Warning System (LDWS) is a kind of system which can relieve the stress of the drivers and reduce traffic accidents. But most traffic scenes have greater dynamic range than the digital camera at present. It makes the accuracy of the system would be affected by the complicated lighting. Traditional lane detection methods always use a usual image taken by the camera to detect the lane boundary. In this paper, we will use three images with different exposure to merge a high dynamic range (HDR) image and detect the lane in the HDR image. The experimental results show that the high dynamic range image can improve the accuracy of the lane detection method. However, processing of merging HDR image is very time consuming. It makes HDR image can´t be used in real-time LDWS. We proposed an improved method based on exposure fusion to reduce the computational time of the system.
Keywords :
alarm systems; driver information systems; image fusion; merging; object detection; road accidents; street lighting; video cameras; video surveillance; HDR image merging; LDWS; camera; exposure fusion; high dynamic range image; lane boundary detection; lane departure warning system; lighting; traffic scene; vehicle departure accident; Cameras; Dynamic range; Histograms; Image edge detection; Merging; Real time systems; Roads; Autonomous Vehicle; Computer Vision; HDR image; Lane Detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Informatics (INDIN), 2012 10th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-0312-5
Type :
conf
DOI :
10.1109/INDIN.2012.6301367
Filename :
6301367
Link To Document :
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