One-against-all-based multiclass SVM strategies applied to vehicle plate character recognition

Authors:
Tiago C. Mota;Antonio Carlos G. Thomé
Affiliations:
Mathematics Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil;Mathematics Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

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Abstract

This work describes a study of strategies for classification of characters extracted from vehicle plate images. We propose to make use of Support Vector Machines, as well as strategies for building multiclassifiers from this model. The proposed strategies are based on the well-known One-Against-All approach and, beyond multiclassifier building, they have as main idea the mapping of the outputs of the binary classifiers that constitutes the multiclassifier. We describe the tests of applying the proposed strategies to the cited problem and expose results that show a significant performance improvement.