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Traffic sign shape classification evaluation. Part II. FFT applied to the signature of blobs

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5 Author(s)
Gil-Jimenez, P. ; Dept. de Teoria de la Senal y Comunicaciones, Univ. de Alcala, Alcala de Henares, Madrid, Spain ; Lafuente-Arroyo, S. ; Gomez-Moreno, H. ; Lopez-Ferreras, F.
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In this paper we have developed a new algorithm of artificial vision oriented to traffic sign shape classification. The classification method basically consists of a series of comparison between the FFT of the signature of a blob and the FFT of the signatures of the reference shapes used in traffic signs. The two major steps of the process are: the segmentation according to the color and the identification of the geometry of the candidate blob using its signature. The most important advances are its robustness against rotation and deformation due to camera projections.

Published in:

Intelligent Vehicles Symposium, 2005. Proceedings. IEEE

Date of Conference:

6-8 June 2005