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Background on Traffic Sign Detection and Recognition

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Traffic-Sign Recognition Systems

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

Abstract

The automatic sign detection and recognition has been converted to a real challenge for high performance of computer vision and machine learning techniques. Traffic sign analysis can be divided in three main problems: automatic location, detection and categorization of traffic signs. Basically, most of the approaches in locating and detecting of traffic signs are based on color information extraction. A natural question arises: which is the most proper color space to assure robust color analysis without influence of the exterior environment. Given the strong dependence on weather conditions, shadows and time of the day, some autors focus on the shape-based sign detection (e.g. Hough transform, ad-hoc models based on Canny edges or convex hulls). Recognition of traffic signs has been addressed by a large amount of classification techniques: from simple template matching (e.g. cross-correlation similarity), to sophisticated Machine learning techniques (e.g. suport vector machines, boosting, random forest, etc), are among strong candidates to assure straightforward outcome necessary for a real end-user system. Moreover, extending the traffic sign analysis from isolated frames to videos can allow to significantly reduce the number of false alarm ratio as well as to increase the precision and the accuracy of the detection and recognition process.

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Authors and Affiliations

  1. Department of Applied Mathematics and Analysis, University of Barcelona, Gran Via de les Corts Catalanes 585, 08007, Barcelona, Spain

    Sergio Escalera, Oriol Pujol, Jordi Vitrià & Petia Radeva

  2. Department of Computer Science, Universitat Oberta de Catalunya, Rambla del Poblenou, 158, Barcelona, Spain

    Xavier Baró

Authors
  1. Sergio Escalera
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  2. Xavier Baró
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  3. Oriol Pujol
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  4. Jordi Vitrià
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  5. Petia Radeva
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Correspondence to Sergio Escalera .

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© 2011 Sergio Escalera

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Escalera, S., Baró, X., Pujol, O., Vitrià, J., Radeva, P. (2011). Background on Traffic Sign Detection and Recognition. In: Traffic-Sign Recognition Systems. SpringerBriefs in Computer Science. Springer, London. https://doi.org/10.1007/978-1-4471-2245-6_2

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  • DOI: https://doi.org/10.1007/978-1-4471-2245-6_2

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-2244-9

  • Online ISBN: 978-1-4471-2245-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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