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Efficient method for vehicle license plate identification based on learning a morphological feature

机译:基于形态学特征的高效车牌识别方法

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摘要

The detection and identification of license plates from captured images have been widely studied over the past two decades. The demand for this technology in security and commercial applications ranges from traffic control organisation to parking management and vehicle tracking. License plate recognition can be divided into two steps: detection and identification. Recent algorithms have focused on the detection step, with few researchers studying identification. In this study, an algorithm is developed to detect and identify license plates. The algorithm is based on the fact that license plates have a semi-symmetric distribution of corner points; it utilises morphological feature learning. The algorithm runs in real time, is highly robust, and can identify whether the candidate region contains a license plate.
机译:在过去的二十年中,从捕获的图像中检测和识别车牌已经得到了广泛的研究。在安全和商业应用中对该技术的需求范围从交通控制组织到停车管理和车辆跟踪。车牌识别可以分为两个步骤:检测和识别。最近的算法专注于检测步骤,很少有研究人员研究鉴定。在这项研究中,开发了一种算法来检测和识别车牌。该算法基于以下事实:车牌具有拐角点的半对称分布。它利用形态特征学习。该算法实时运行,具有很高的鲁棒性,并且可以识别候选区域是否包含车牌。

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