Title :
Image segmentation based road sign detection
Author :
Khan, Jesmin F. ; Adhami, Reza R. ; Bhuiyan, Sharif M A
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Alabama in Huntsville, Huntsville, AL, USA
Abstract :
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.
Keywords :
image classification; image colour analysis; image recognition; image segmentation; road traffic; fringe-adjusted joint transform correlation technique; geometric shape information; image color features; image recognition; image segmentation; road traffic sign detection; shape classification criteria; Brightness; Clustering algorithms; Frequency; Gabor filters; Image databases; Image segmentation; Layout; Roads; Shape; Spatial databases; Clustering; feature extraction; fringe-adjusted filter; joint transform correlation; segmentation;
Conference_Titel :
Southeastcon, 2009. SOUTHEASTCON '09. IEEE
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-3976-8
Electronic_ISBN :
978-1-4244-3978-2
DOI :
10.1109/SECON.2009.5174040