Traffic Sign Detection and Pattern Recognition Based on Binary Tree Support Vector Machines

Abstract:

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This paper presents an automatic road sign detection and recognition system based on binary tree SVM. Color based segmentation techniques are employed for traffic sign detection. The coordinates position of traffic sign in images used for shape classification are obtained by orthogonal projection. An algorithm based on Hough transform was proposed to achieve better shape classification performance.Recognition of traffic signs are implemented using binary tree multi- classifer SVM with geometry semantic feature as the feature vector

Info:

Periodical:

Advanced Materials Research (Volumes 204-210)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

1394-1398

DOI:

10.4028/www.scientific.net/AMR.204-210.1394

Citation:

F. M. Gong and H. J. Li, "Traffic Sign Detection and Pattern Recognition Based on Binary Tree Support Vector Machines", Advanced Materials Research, Vols. 204-210, pp. 1394-1398, 2011

Online since:

February 2011

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Price:

$35.00

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