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License Plate Location for Vehicles Passing through a Gate

机译:穿过大门的车辆的车牌位置

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摘要

This paper is dedicated to a license plate location method for moving vehicles passing through a gate in various weather conditions. The proposed license plate location algorithm mainly consists of edge detection, binarization, and license-plate judgment. Based on histogram analysis of a gradient image, the possible position of license plate is located from the image through the proposed effective edge detection. From those license-plate candidate regions, the correct position of the license plate is selected by the horizontal projection. In order to correctly extract the license plate in the sunny, cloudy and raining weathers, an adaptive binarization method is developed for substantially preserving edges of a license plate. Experimental results show that the proposed license plate location with low-complexity has good performance in locating the license plate of moving vehicles for various weathers. For vehicles passing through a gate at different speeds, the license plate location rates is above 90% on average for various weather conditions including the sunny situation, cloudy situation, and raining situation.
机译:本文致力于在各种天气条件下移动通过大门的车辆的车牌定位方法。提出的车牌定位算法主要包括边缘检测,二值化和车牌判断。通过对梯度图像进行直方图分析,可以通过提出的有效边缘检测从图像中找到车牌的可能位置。从那些车牌候选区域中,通过水平投影选择车牌的正确位置。为了在晴朗,多云和下雨的天气中正确提取车牌,开发了一种自适应二值化方法以基本上保留车牌的边缘。实验结果表明,所提出的低复杂度的车牌定位在各种天气条件下对移动车辆的车牌定位具有良好的性能。对于以不同速度通过大门的车辆,在各种天气条件下(包括晴天,阴天和下雨情况),车牌定位率平均高于90%。

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