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Vehicle License Plate Tilt Correction Based on the Straight Line Fitting Method and Minimizing Variance of Coordinates of Projection Points

Kaushik Deb, Andrey Vavilin, Jung-Won Kim, and Kang-Hyun Jo*
International Journal of Control, Automation, and Systems, vol. 8, no. 5, pp.975-984, 2010

Abstract : Tilt correction is a very crucial and inevitable task in the automatic recognition of the vehicle license plate (VLP). 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 es-timated. 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. Character segmentation is performed after horizontal correction and character points are projected along the vertical direction after shear transform. 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 la-beling algorithm for solving this problem and detecting candidate regions. According to different col-ored LP, these candidate regions may include LP regions. Geometrical properties of the LP such as area, bounding box and aspect-ratio are then used for classification. Various LP images were used with a va-riety of conditions to test the proposed method and results are presented to prove its effectiveness.

Keyword : Least square fitting with perpendicular offsets (LSFPO), minimum variance, recursive labeling algorithm, shear transform, tilt correction, vehicle license plate (VLP).

 
 
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