Knowledge modeling for the traffic sign recognition task

  • Authors:

  • M. Rincón;S. Lafuente-Arroyo;S. Maldonado-Bascón

  • Affiliations:

  • Dpto. de Inteligencia Artificial, ETSI Informatica, UNED, Madrid, Spain;Dpto. de Teoría de la Señal y Comunicaciones, Escuela Politécnica Superior, Universidad de Alcalá, Madrid, Spain;Dpto. de Teoría de la Señal y Comunicaciones, Escuela Politécnica Superior, Universidad de Alcalá, Madrid, Spain

  • Venue:
  • IWINAC'05 Proceedings of the First international conference on Mechanisms, Symbols, and Models Underlying Cognition: interplay between natural and artificial computation - Volume Part I
  • Year:
  • 2005

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Abstract

In this paper we analyse the problem of traffic sign recognition at the knowledge level. Due to the complexity of the task, our approach decomposes it into simpler subtasks until the primitive level is reached. The task has been modeled at the knowledge level as a hierarchical classification task. This has allowed to discover a simple and robust Problem Solving Method (PSM) for the classification task which is reused along different classification stages of the process. The resulting system is divided into three main subtasks: image segmentation according to color, classification of the geometry of the candidate blobs and identification of the specific type of traffic sign. Finally, the system has been evaluated and the results are presented.