This paper proposes an algorithm for real-time license plate detection. In this algorithm, the relatively easy car plate features are adopted including the simple statistical feature and Harr-like feature. The simplicity of the object features used is very helpful to real-time processing. The classifiers based on statistical features decrease the complexity of the system. They are followed by the classifiers based on Haar-like features, which makes the final classifier invariant to the brightness, color, size and position of license plates. The experimental results obtained by the proposed algorithm exhibit the encouraging performance. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Zhang, H., Jia, W., He, X., & Wu, Q. (2006). Real-time license plate detection under various conditions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4159 LNCS, pp. 192–199). Springer Verlag. https://doi.org/10.1007/11833529_20
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