DocumentCode :
3523941
Title :
Road lane recognition system for RCAS
Author :
Yamada, Kenichi ; Ito, Toshio ; Nishioka, Kunio
Author_Institution :
Div. of Electron. Eng., Daihatsu Motor Co. Ltd., Osaka, Japan
fYear :
1996
fDate :
19-20 Sep 1996
Firstpage :
177
Lastpage :
182
Abstract :
Road-lane recognition is one of the key technologies utilized in the intelligent transport system, a sophisticated road traffic information system in Japan. In this paper, we take a general view of road-lane recognition methods that use image processing with reference to the recognition frames of capturing, conversion, classification and interpretation. While these recognition methods employ a bottom-up processing approach, we believe a top-down processing approach based on prior knowledge of the recognition target will play a more important role in the future. One of the purposes of road-lane recognition in rear-end collision avoidance system (RCAS) is to determine whether the vehicle in front is in the same lane or not. As a solution to that question, we introduce a network type fusion method, which divides a recognition process into modules connected in a network and then uses the changes of state obtained in mutual tests to determine the vehicle´s position relative to the road lane
Keywords :
computer vision; image classification; image segmentation; object recognition; road vehicles; image capturing; image classification; image conversion; image processing; intelligent transport system; network type fusion method; object recognition; rear-end collision avoidance system; road lane recognition system; segmentation; top-down processing; Automatic control; Automobiles; Charge coupled devices; Image converters; Image processing; Image recognition; Remotely operated vehicles; Road vehicles; Target recognition; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium, 1996., Proceedings of the 1996 IEEE
Conference_Location :
Tokyo
Print_ISBN :
0-7803-3652-6
Type :
conf
DOI :
10.1109/IVS.1996.566374
Filename :
566374
Link To Document :
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