DocumentCode :
2486620
Title :
Illumination invariant lane color recognition by using road color reference & neural networks
Author :
Choi, Hyun-Chul ; Oh, Se-young
Author_Institution :
Dept. of Electron. & Electr. Eng., Pohang Univ. of Sci. & Technol. (POSTECH), Pohang, South Korea
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
5
Abstract :
Non-linearity of color changing in various lighting conditions is one of the primary factors which make lane color recognition difficult. This paper introduces an illumination invariant lane color recognition method which can recognize two lane colors (white, yellow) and copes with the non-linearity by using neural networks. Our method utilizes the road texture as the indicator of illumination condition and learns the relation between illumination condition and lane color by using multi-layer perceptron. The proposed method was verified by the experiment with a road images sequence of real driving situation.
Keywords :
image colour analysis; image sequences; learning (artificial intelligence); multilayer perceptrons; road traffic; illumination invariant lane color recognition; lighting conditions; multilayer perceptron; neural networks; road color reference; road image sequence; road texture; Equations; Image color analysis; Lighting; Mathematical model; Pixel; Roads; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
ISSN :
1098-7576
Print_ISBN :
978-1-4244-6916-1
Type :
conf
DOI :
10.1109/IJCNN.2010.5596304
Filename :
5596304
Link To Document :
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