%0 Journal Article
%T Traffic sign recognition system with β -correction
%A Sergio Escalera
%A Oriol Pujol
%A Petia Radeva
%J Machine Vision and Applications
%D 2010
%V 21
%N 2
%I Springer-Verlag
%@ 0932-8092
%F Sergio Escalera2010
%O MILAB;HUPBA
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1276), last updated on Thu, 18 Jan 2018 12:02:06 +0100
%X 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.
%U http://dx.doi.org/10.1007/s00138-008-0145-z
%P 99–111