Paper Title:
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.

  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, W. Z. Liang, S. Q. Xu, F. Z. Li, "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
$32.00
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