Traffic Sign Recognition Based on SIFT Features

Ni An Cai; Wen Zhao Liang; Shao Qiu Xu; Fang Zhen Li

doi:10.4028/www.scientific.net/AMR.121-122.596

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 121-122Traffic Sign Recognition Based on SIFT Features

Traffic Sign Recognition Based on SIFT Features

Abstract:

A recognition method for traffic signs based on an SIFT features is proposed to solve the problems of distortion and occlusion. SIFT features are first extracted from traffic signs and matched by using the Euclidean distance. Then the recognition is implemented based on the similarity. Experimental results show that the proposed method, superior to traditional method, can excellently recognize traffic signs with the transformation of scale, rotation, and distortion and has a good ability of anti-noise and anti-occlusion.

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Periodical:

Advanced Materials Research (Volumes 121-122)

Pages:

596-599

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.121-122.596

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Online since:

June 2010

Authors:

Ni An Cai, Wen Zhao Liang, Shao Qiu Xu, Fang Zhen Li

Keywords:

Decision Tree, Distortion, Occlusion, SIFT Features, Traffic Sign Recognition

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