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
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