Machine Vision and Applications

, Volume 21, Issue 2, pp 99–111 | Cite as

Traffic sign recognition system with β -correction

Original Paper

Abstract

Traffic sign classification represents a classical application of multi-object recognition processing in uncontrolled adverse environments. Lack of visibility, illumination changes, and partial occlusions are just a few problems. In this paper, we introduce a novel system for multi-class classification of traffic signs based on error correcting output codes (ECOC). ECOC is based on an ensemble of binary classifiers that are trained on bi-partition of classes. We classify a wide set of traffic signs types using robust error correcting codings. Moreover, we introduce the novel β-correction decoding strategy that outperforms the state-of-the-art decoding techniques, classifying a high number of classes with great success.

Keywords

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

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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Department Ciències de la ComputacióComputer Vision Center, UABBellaterraSpain
  2. 2.Department Matemàtica Aplicada i AnàlisiUBBarcelonaSpain

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