DocumentCode
999833
Title
Visual sign information extraction and identification by deformable models for intelligent vehicles
Author
de la Escalera, A. ; Armingol, José María ; Pastor, José Manuel ; Rodríguez, Francisco José
Author_Institution
Dept. of Syst. Eng. & Autom., Univ. Carlos de Madrid, Leganes, Spain
Volume
5
Issue
2
fYear
2004
fDate
6/1/2004 12:00:00 AM
Firstpage
57
Lastpage
68
Abstract
This paper deals with the extraction of part of the visual information presented in streets, roads, and motorways. This information, provided by either traffic or road signs and route-guidance signs, is extremely important for safe and successful driving. An automatic system that is capable of extracting and identifying these signs automatically would help human drivers enormously; navigation would be easier and would allow him or her to concentrate on driving the vehicle. The system would indicate to the driver the presence of a sign in advance, so that some incorrect human decisions could be avoided. A deformable model scheme allows us to include the knowledge used while designing the signs in the algorithm and is used for their detection and identification. Two techniques to find the minimum in the energy function are shown: simulated annealing and genetic algorithms. Some problems are addressed, such as uncontrolled lighting conditions; occlusions; and variations in shape, size, and color.
Keywords
decision support systems; driver information systems; genetic algorithms; image recognition; road traffic; simulated annealing; advanced driver assistance systems; deformable models; energy function; genetic algorithms; intelligent vehicles; navigation; simulated annealing; visual sign information extraction; visual sign information identification; Algorithm design and analysis; Data mining; Deformable models; Humans; Intelligent vehicles; Navigation; Roads; Simulated annealing; Traffic control; Vehicle driving; ADASs; Advance driver-assistance systems; deformable models; intelligent vehicles; traffic sign recognition;
fLanguage
English
Journal_Title
Intelligent Transportation Systems, IEEE Transactions on
Publisher
ieee
ISSN
1524-9050
Type
jour
DOI
10.1109/TITS.2004.828173
Filename
1303537
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