Real-time recognition of license plates of moving vehicles in Sri Lanka

A. Wijetunge, D. Ratnaweera
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引用次数: 10

Abstract

Automated license plate recognition can be used for many applications such as detecting traffic light violations, access controlling, calculating parking fee and so on. However, detection and recognition of license plates can be seen as a complex problem. This paper presents an algorithm which can be used in Sri Lanka, for detecting and recognizing license plates automatically using image processing and neural networks techniques. In the proposed algorithm, the license plates are located by analyzing the regions with highest vertical edge density. Hough transformation and the affine transformation techniques are used to handle the skewed license plates. After extracting the license plate characters, a neural network is used to recognize those characters. The experimental results show that the proposed system can successfully detect and recognize all types of license plates in Sri Lanka and is suitable for real time implementation because of the lower execution time.
斯里兰卡移动车辆车牌的实时识别
自动车牌识别可以用于许多应用,如检测交通灯违规,门禁,计算停车费用等。然而,车牌的检测和识别可以被视为一个复杂的问题。本文提出了一种基于图像处理和神经网络技术的车牌自动检测和识别算法,该算法可用于斯里兰卡。该算法通过分析垂直边缘密度最大的区域来定位车牌。采用霍夫变换和仿射变换技术对倾斜车牌进行处理。在提取车牌字符后,利用神经网络对车牌字符进行识别。实验结果表明,该系统可以成功地检测和识别斯里兰卡所有类型的车牌,并且由于执行时间较短,适合实时实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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