Traffic-Sign Recognition Systems

  • Sergio Escalera
  • Xavier Baró
  • Oriol Pujol
  • Jordi Vitrià
  • Petia Radeva

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-vi
  2. Sergio Escalera, Xavier Baró, Oriol Pujol, Jordi Vitrià, Petia Radeva
    Pages 1-4
  3. Sergio Escalera, Xavier Baró, Oriol Pujol, Jordi Vitrià, Petia Radeva
    Pages 5-13
  4. Sergio Escalera, Xavier Baró, Oriol Pujol, Jordi Vitrià, Petia Radeva
    Pages 15-52
  5. Sergio Escalera, Xavier Baró, Oriol Pujol, Jordi Vitrià, Petia Radeva
    Pages 53-80
  6. Sergio Escalera, Xavier Baró, Oriol Pujol, Jordi Vitrià, Petia Radeva
    Pages 81-94
  7. Sergio Escalera, Xavier Baró, Oriol Pujol, Jordi Vitrià, Petia Radeva
    Pages 95-96

About this book

Introduction

This work presents a full generic approach to the detection and recognition of traffic signs. The approach, originally developed for a mobile mapping application, is based on the latest computer vision methods for object detection, and on powerful methods for multiclass classification. The challenge was to robustly detect a set of different sign classes in real time, and to classify each detected sign into a large, extensible set of classes. To address this challenge, several state-of-the-art methods were developed that can be used for different recognition problems. Following an introduction to the problems of traffic sign detection and categorization, the text focuses on the problem of detection, and presents recent developments in this field. The text then surveys a specific methodology for the problem of traffic sign categorization – Error-Correcting Output Codes – and presents several algorithms, performing experimental validation on a mobile mapping application. The work ends with a discussion on future lines of research, and continuing challenges for traffic sign recognition.

Keywords

Adaboost Embedding of dichotomizers Error correcting output codes Multi-class classification Object recognition Traffic sign classification

Authors and affiliations

  • Sergio Escalera
    • 1
  • Xavier Baró
    • 2
  • Oriol Pujol
    • 3
  • Jordi Vitrià
    • 4
  • Petia Radeva
    • 5
  1. 1.Dept. of Applied Mathematics & AnalysisUniversity of BarcelonaBarcelonaSpain
  2. 2.Universitat Oberta de CatalunyaDepartment of Computer ScienceRambla del PoblenouSpain
  3. 3.Dept of Applied Mathematics and AnalysisUniversity of BarcelonaGran Via de les Corts CatalanesSpain
  4. 4.University of BarcelonaDept of Applied Mathematics and AnalysisGran Via de les Corts CatalanesSpain
  5. 5.University of BarcelonaDept of Applied Mathematics and AnalysisGran Via de les Corts CatalanesSpain

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-2245-6
  • Copyright Information Sergio Escalera 2011
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-4471-2244-9
  • Online ISBN 978-1-4471-2245-6
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • About this book