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Chinese License Plate Localization in Multi-Lane with Complex Background Based on Concomitant Colors

机译:基于伴随颜色的复杂背景多车道中文车牌定位

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摘要

Color is an important feature of the Chinese license plate. In this paper, a license plate location method totally based on color information for the most common blue and yellow plates is proposed. First, use a special way to generate a grayscale image, highlighting the blue and yellow regions of the original image. Then by using the color concomitant property and transitions between the background and the characters, fake plates are removed, and real plates reserved. Finally, use the color information again to get a more accurate location result and remove the fake plates by using the relationship between the stroke width and the character size. The proposed method adopts two kinds of threshold methods: global threshold method and adaptive block threshold method. By automatically judging the illumination distribution of an image, the algorithm can decide which to use. The proposed method can be used to locate license plates in multi-lane with complex background, and works well even on images with uneven illumination. 2207 images from different traffic videos are used to do experiments, including 1314 images of daytime and 893 images of nighttime. Each image contains 0-7 plates, and the location rate achieves 95.01%.
机译:颜色是中国车牌的重要特征。本文提出了一种完全基于颜色信息的最常见的蓝色和黄色车牌定位方法。首先,使用一种特殊的方法来生成灰度图像,突出显示原始图像的蓝色和黄色区域。然后,通过使用颜色伴随属性以及背景和字符之间的过渡,可以删除假版,并保留真实版。最后,再次使用颜色信息以获得更准确的定位结果,并通过使用笔划宽度和字符大小之间的关系来删除假版。所提出的方法采用两种阈值方法:全局阈值方法和自适应块阈值方法。通过自动判断图像的照度分布,算法可以决定使用哪个。所提出的方法可用于在背景复杂的多车道上定位车牌,即使在光照不均匀的图像上也能很好地工作。来自不同交通视频的2207张图像用于进行实验,包括1314张白天的图像和893张夜间的图像。每个图像包含0-7个板,定位率达到95.01%。

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