首页> 外文期刊>International Journal of Control, Automation, and Systems >Vehicle License Plate Tilt Correction Based on the Straight Line Fitting Method and Minimizing Variance of Coordinates of Projection Points
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Vehicle License Plate Tilt Correction Based on the Straight Line Fitting Method and Minimizing Variance of Coordinates of Projection Points

机译:基于直线拟合方法并最小化投影点坐标方差的车牌倾斜校正

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摘要

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 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. 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 labeling algorithm for solving this problem and detecting candidate regions. According to different colored 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 variety of conditions to test the proposed method and results are presented to prove its effectiveness.
机译:倾斜校正是自动识别车牌(VLP)的非常关键且不可避免的任务。在本文中,根据具有垂直偏移的最小二乘拟合(LSFPO),将VLP区域拟合为一条直线。在获得线斜率之后,估计VLP的旋转角度。然后旋转整个图像以在水平方向上倾斜此角度以进行倾斜校正。提出了通过最小化投影点的坐标方差在垂直方向上的倾斜校正。在水平校正之后执行字符分割,并在剪切变换后沿垂直方向投影字符点。尽管在过去的几十年中VLP检测方法取得了成功,但即使车身和LP具有相似的颜色,它们中的一些仍可以有效地定位车牌(LP)。基于颜色的VLP检测的常见缺点是无法检测LP的边界或边界。在本文中,我们提出了一种改进的递归标记算法来解决该问题并检测候选区域。根据不同颜色的LP,这些候选区域可以包括LP区域。然后将LP的几何属性(例如面积,边界框和长宽比)用于分类。在各种条件下使用各种LP图像来测试该方法,并给出结果以证明其有效性。

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