Abstract
This paper presents a new license plate detection algorithm, in which, the Haar and MB-LBP features are combined and the updated rules of the sample weights are revised. The cascade classifiers are used to detect digitals in the image, Non-Maximum Suppression and the license plate characteristics are applied to locate license plate area accurately. Experimental results show that the proposed method could effectively avoid the phenomenon of weights distortions and get higher detection rate while reducing false alarm rate.
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Pan, Q., Shen, J., Yang, W., Sun, C. (2013). Ensemble Haar and MB-LBP Features for License Plate Detection. In: Yang, J., Fang, F., Sun, C. (eds) Intelligent Science and Intelligent Data Engineering. IScIDE 2012. Lecture Notes in Computer Science, vol 7751. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36669-7_28
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DOI: https://doi.org/10.1007/978-3-642-36669-7_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36668-0
Online ISBN: 978-3-642-36669-7
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