By Topic

Image segmentation based road sign detection

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Khan, J.F. ; Dept. of Electr. & Comput. Eng., Univ. of Alabama in Huntsville, Huntsville, AL, USA ; Adhami, R.R. ; Bhuiyan, S.M.A.

This paper proposes an automatic method to detect road traffic signs in natural scenes. There are three main stages in the proposed algorithm: (1) segmentation based on the brightness and color features to find the possible candidate road sign regions; (2) sign detection by using two shape classification criteria; and (3) recognition of the road sign by employing a fringe-adjusted joint transform correlation (FJTC) technique. The proposed framework provides a novel way to detect a road sign by integrating image features with the geometric shape information. Experimental results on real life images demonstrate that the proposed algorithm is invariant to translation, rotation, and scale.

Published in:

Southeastcon, 2009. SOUTHEASTCON '09. IEEE

Date of Conference:

5-8 March 2009