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Shape Classification Algorithm Using Support Vector Machines for Traffic Sign Recognition

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Computational Intelligence and Bioinspired Systems (IWANN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3512))

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Abstract

In this paper, a new algorithm for traffic sign recognition is presented. It is based on a shape detection algorithm that classifies the shape of the content of a sign using the capabilities of a Support Vector Machine (SVM). Basically, the algorithm extracts the shape inside a traffic sign, computes the projection of this shape and classifies it into one of the shapes previously trained with the SVM. The most important advances of the algorithm is its robustness against image rotation and scaling due to camera projections, and its good performance over images with different levels of illumination. This work is part of a traffic sign detection and recognition system, and in this paper we will focus solely on the recognition step.

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Authors and Affiliations

  1. Dpto. de Teoría de la señal y Comunicaciones, Universidad de Alcalá, 28871, Alcalá de Henares (Madrid), Spain

    P. Gil-Jiménez, S. Lafuente-Arroyo, S. Maldonado-Bascón & H. Gómez-Moreno

Authors
  1. P. Gil-Jiménez
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  2. S. Lafuente-Arroyo
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  3. S. Maldonado-Bascón
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  4. H. Gómez-Moreno
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Editors and Affiliations

  1. Departamento de Ingeniería Electrónica, Universitat Politècnica de Catalunya (UPC). E.T.S.I. de Telecomunicación, Campus Norte, Edificio C4, C/ Jordi Girona, 1-3, E08034, Barcelona, Spain

    Joan Cabestany

  2. Department of Computer Architecture and Computer Technology, University of Granada,  

    Alberto Prieto

  3. Grupo ISIS, Dpto. Tecnología Electrónica ETSI Telecomunicación, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Francisco Sandoval

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© 2005 Springer-Verlag Berlin Heidelberg

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Gil-Jiménez, P., Lafuente-Arroyo, S., Maldonado-Bascón, S., Gómez-Moreno, H. (2005). Shape Classification Algorithm Using Support Vector Machines for Traffic Sign Recognition. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_107

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  • DOI: https://doi.org/10.1007/11494669_107

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26208-4

  • Online ISBN: 978-3-540-32106-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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