Abstract
Tilt correction is an integrant part of the automatic vehicle license plate recognition (VLPR) system. In this paper, according to the least square fitting with perpendicular offsets (LSFPO) the VLP region is fitted to a straight line. After the line slope is obtained, rotation angle of the VLP is estimated. Then the whole image is rotated for tilt correction in horizontal direction by this angle. Tilt correction in vertical direction by minimizing the variance of coordinates of the projection points is proposed. Despite the success of VLP detection approaches in the past decades, a few of them can effectively locate license plate (LP), even when vehicle bodies and LPs have similar color. A common drawback of color-based VLP detection is the failure to detect the boundaries or border of LPs. In this paper, we propose a modified recursive labeling algorithm for solving this problem and detecting candidate regions. While conducting the experiment, vehicle images taken under various conditions from traffic stations to evaluate the robustness, the flexibility and effectiveness.
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References
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Deb, K., Vavilin, A., Kim, JW., Jo, KH. (2010). License Plate Tilt Correction Based on the Straight Line Fitting Method and Projection. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6423. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16696-9_20
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DOI: https://doi.org/10.1007/978-3-642-16696-9_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16695-2
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