Traffic Sign Recognition Based on SIFT Features

Abstract:

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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.

Info:

Periodical:

Advanced Materials Research (Volumes 121-122)

Edited by:

Donald C. Wunsch II, Honghua Tan, Dehuai Zeng, Qi Luo

Pages:

596-599

DOI:

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

Citation:

N. A. Cai et al., "Traffic Sign Recognition Based on SIFT Features", Advanced Materials Research, Vols. 121-122, pp. 596-599, 2010

Online since:

June 2010

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Price:

$35.00

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