Abstract
License Plate Recognition (LPR) is used in various security and traffic applications. This paper introduces a LPR system using morphological operations and edge detection for plate localization and characters segmentation. To emphasize the importance of classification reliability that is essential for reducing the cost caused by incorrect decisions, a cascaded classification system is designed, which consists of two modules, i.e., local mean k-nearest neighbor and one-versus-all support vector machine, each with reject option controlled by a properly defined reliability parameter. The impact of using the proposed cascade scheme is evaluated in terms of the trade-off between the rejection rate and classification accuracy. Experimental results confirm the effectiveness of the proposed system.
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The project is supported by Suzhou Municipal Science and Technology Foundation Grants SS201109 and SYG201140.
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Zhang, B., Pan, H., Li, Y., Xu, L. (2014). Reliable License Plate Recognition by Cascade Classifier Ensemble. In: Patnaik, S., Li, X. (eds) Proceedings of International Conference on Computer Science and Information Technology. Advances in Intelligent Systems and Computing, vol 255. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1759-6_80
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DOI: https://doi.org/10.1007/978-81-322-1759-6_80
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-1758-9
Online ISBN: 978-81-322-1759-6
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