Traffic sign recognition system with β -correction
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- Escalera, S., Pujol, O. & Radeva, P. Machine Vision and Applications (2010) 21: 99. doi:10.1007/s00138-008-0145-z
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.
KeywordsMulti-class classification Error correcting output codes Embedding of dichotomizers Object recognition Traffic sign classification Adaboost
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