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A Fast Algorithm for License Plate Detection

机译:一种快速的车牌检测算法

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摘要

In this paper we propose a method for detection of the car license plates in 2D gray images. In this method we first estimate the density of vertical edges in the image. The regions with high density vertical edges are good candidates for license plates. In order to filter out clutter regions possessing similar feature in the edge density image, we design a match filter which models the license plate pattern. By applying the proposed filter on the edge density image followed by a thresholding procedure, the locations of license plate candidates are detected. We finally extract the boundary of license plate(s) using the morphological operations. The result of experiments on car images (taken under different imaging conditions especially complex scenes) confirms the ability of the method for license plate detection. As the complexity of the proposed algorithm is low, it is considerably fast.
机译:在本文中,我们提出了一种在2D灰度图像中检测汽车牌照的方法。在这种方法中,我们首先估计图像中垂直边缘的密度。具有高密度垂直边缘的区域是牌照的理想选择。为了滤除边缘密度图像中具有相似特征的杂波区域,我们设计了一个匹配滤波器,该滤波器对车牌图案进行建模。通过在边缘密度图像上应用建议的滤镜,然后进行阈值处理,可以检测到车牌候选的位置。最后,我们使用形态学运算来提取车牌的边界。汽车图像的实验结果(在不同的成像条件下,尤其是在复杂的场景下拍摄)证实了该方法的能力。由于所提出算法的复杂度较低,因此相当快。

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