DocumentCode :
1941851
Title :
Traffic sign shape classification evaluation. Part II. FFT applied to the signature of blobs
Author :
Gil-Jiménez, P. ; Lafuente-Arroyo, S. ; Gómez-Moreno, H. ; López-Ferreras, F. ; Maldonado-Bascón, S.
Author_Institution :
Dept. de Teoria de la Senal y Comunicaciones, Univ. de Alcala, Alcala de Henares, Madrid, Spain
fYear :
2005
fDate :
6-8 June 2005
Firstpage :
607
Lastpage :
612
Abstract :
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.
Keywords :
cameras; computer vision; fast Fourier transforms; image classification; image segmentation; road traffic; FFT; artificial vision; camera projections; candidate blob signature; traffic sign shape classification evaluation; Color; Electronic mail; Geometry; Image databases; Image recognition; Image segmentation; Robustness; Shape; Testing; Traffic control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium, 2005. Proceedings. IEEE
Print_ISBN :
0-7803-8961-1
Type :
conf
DOI :
10.1109/IVS.2005.1505170
Filename :
1505170
Link To Document :
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