Image segmentation based road sign detection

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 classific...

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Bibliographic Details
Main Authors: Khan, J.F., Adhami, R.R., Bhuiyan, S.M.A.
Format: Conference Proceeding
Language:English
Subjects:
Brightness
Clustering
Clustering algorithms
feature extraction
Frequency
fringe-adjusted filter
Gabor filters
Image databases
Image segmentation
joint transform correlation
Layout
Roads
segmentation
Shape
Spatial databases
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Description
Summary: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.
ISSN:1091-0050
1558-058X
DOI:10.1109/SECON.2009.5174040