Title :
Road detection using segmentation by weighted aggregation based on visual information and a posteriori probability of road regions
Author :
Son, T.T. ; Mita, S. ; Takeuchi, A.
Author_Institution :
Dept. of Electron. & Inf., Toyota Technol. Inst., Nagoya
Abstract :
In this paper, a road detection method based on an image segmentation algorithm is presented. Road detection process is a key issue for an autonomous driving system in urban environment. Image-based road detection algorithm is applied on sources of visual information recorded by cameras when our car is running on road. Our method combines a posteriori probability and visual information for image segmentation. The method is composed of two steps. Firstly, a road identifier is trained with supervised learning algorithm. Secondly, road regions are detected by combining a posteriori probability and visual information using image segmentation algorithm. Experimental results are presented for road images in actual driving video acquired in urban areas.
Keywords :
driver information systems; image segmentation; object detection; probability; roads; traffic engineering computing; a posteriori probability; autonomous driving system; image segmentation; image-based road detection; road regions; urban environment; visual information; weighted aggregation; Cameras; Detection algorithms; Image edge detection; Image segmentation; Laser modes; Roads; Robustness; Supervised learning; Surface texture; Urban areas; Road detection; image segmentation; road region; variance image;
Conference_Titel :
Systems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-2383-5
Electronic_ISBN :
1062-922X
DOI :
10.1109/ICSMC.2008.4811758
