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An Efficient Method for Vehicle License Plate Detection in Complex Scenes

机译:一种复杂场景下车牌检测的有效方法

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In this paper, we propose an efficient method for license plate localization in the images with various situations and complex background. At the first, in order to reduce problems such as low quality and low contrast in the vehicle images, image contrast is enhanced by the two different methods and the best for following is selected. At the second part, vertical edges of the enhanced image are extracted by sobel mask. Then the most of the noise and background edges are removed by an effective algorithm. The output of this stage is given to a morphological filtering to extract the candidate regions and finally we use several geometrical features such as area of the regions, aspect ratio and edge density to eliminate the non-plate regions and segment the plate from the input car image. This method is performed on some real images that have been captured at the different imaging conditions. The appropriate experimental results show that our proposed method is nearly independent to environmental conditions such as lightening, camera angles and camera distance from the automobile, and license plate rotation.
机译:在本文中,我们提出了一种在各种情况和复杂背景下对图像进行车牌定位的有效方法。首先,为了减少诸如在车辆图像中的低质量和低对比度的问题,通过两种不同的方法来增强图像对比度,并选择最佳跟随方法。在第二部分,通过sobel遮罩提取增强图像的垂直边缘。然后通过有效的算法去除大部分噪声和背景边缘。该阶段的输出经过形态滤波,以提取候选区域,最后我们使用一些几何特征(例如区域的面积,纵横比和边缘密度)来消除非板块区域,并从输入车中分割出板块图片。对在不同成像条件下捕获的一些真实图像执行此方法。适当的实验结果表明,我们提出的方法几乎不受环境条件的影响,例如减光,摄像头角度和距汽车的摄像头距离以及牌照旋转。

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