DocumentCode :
2797198
Title :
Color vision-based multi-level analysis and fusion for road area detection
Author :
Wu, Xiaowen ; Peng, Yuxin ; Ding, Donghua ; Liu, Huaping ; He, Kezhong ; Sun, Fuchun
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing
fYear :
2008
fDate :
4-6 June 2008
Firstpage :
602
Lastpage :
607
Abstract :
This paper presents an integrated approach to robust analysis of road area images in front of the car from a single color camera. In order to get more information from the image source, we build a three-level data fusion based on Dempster-Shaferpsilas decision theory. During the first level, we separate the input image into perspective view and birdpsilas view and recognize small road patches from the background using color histogram features. In the second level we fuse the evidences from each recognized patch and re-calculate the road-like probabilities in each view. The third level is to merge the results of the two views into one birdpsilas-view segmentation map to achieve a high degree of reliability. Our Bagging-like method has been tested in real world environments and the fusion results have been shown to be robust to road textures, trees and moving objects in the scene.
Keywords :
automated highways; colour vision; image colour analysis; inference mechanisms; object detection; reliability; roads; Dempster-Shafer decision theory; bagging-like method; color histogram features; color vision-based multi-level analysis; reliability; road area detection; road area images; road-like probabilities; robust analysis; three-level data fusion; Cameras; Decision theory; Fuses; Histograms; Image analysis; Image color analysis; Image recognition; Roads; Robustness; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium, 2008 IEEE
Conference_Location :
Eindhoven
ISSN :
1931-0587
Print_ISBN :
978-1-4244-2568-6
Electronic_ISBN :
1931-0587
Type :
conf
DOI :
10.1109/IVS.2008.4621146
Filename :
4621146
Link To Document :
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