Abstract
A robust method for plate segmentation in a License Plate Recognition (LPR) system is presented, designed to work in a wide range of acquisition conditions, including unrestricted scene environments, light, perspective and camera-to-car distance. Although this novel text-region segmentation technique has been applied to a very specific problem, it is extensible to more general contexts, like difficult text segmentation tasks dealing with natural images. Extensive experimentation has been performed in order to estimate the best parameters for the task at hand, and the results obtained are presented.
Work partially supported by the Spanish CICYT under grant TIC2000-1703-CO3-01
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Cano, J., Pérez-Cortés, JC. (2003). Vehicle License Plate Segmentation in Natural Images. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_17
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DOI: https://doi.org/10.1007/978-3-540-44871-6_17
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