Traffic sign recognition system with β -correction |
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Authors: | Sergio Escalera Oriol Pujol Petia Radeva |
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Affiliation: | 1. Department Ciències de la Computació, Computer Vision Center, UAB, 08193, Bellaterra, Spain 2. Department Matemàtica Aplicada i Anàlisi, UB, Gran Via 585, 08007, Barcelona, Spain
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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. |
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Keywords: | |
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