Automatic car registration plate recognition using fast Hough transform

S. Gendy, C. Smith, S. Lachowicz
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引用次数: 21

Abstract

The development of automatic car registration plate recognition will provide greater efficiency for vehicle monitoring in automatic zone access control. Plate recognition will avoid the need to equip vehicles with special RF tags, since all vehicles possess a unique registration number plate. Also the proposed recognition system can be used in conjunction with a tag system for higher security. There are a number of techniques which have been used for car registration plate characters recognition. These systems include BAM (Bi-directional Associative Memories) neural network character recognition and pattern matching of characters as two character recognition techniques which will be discussed in this paper. The object of this paper is to explore the potential of using Fast Hough Transform (FHT) in vehicle registration plate recognition. Image processing techniques have been used to extract plate characters, then FHT algorithm is applied to every character in the image for recognition and identification. The FHT used in the paper is an efficient, fast and simple algorithm to identify characters, without requiring a relatively large memory.
基于快速霍夫变换的汽车车牌自动识别
车牌自动识别技术的发展将为自动门禁中的车辆监控提供更高的效率。车牌识别将避免为车辆配备特殊的射频标签,因为所有车辆都有一个唯一的注册车牌。此外,所提出的识别系统可以与标签系统结合使用,以提高安全性。有许多技术已被用于汽车车牌字符识别。这些系统包括BAM(双向联想记忆)神经网络字符识别和字符模式匹配作为两种字符识别技术,本文将对此进行讨论。本文旨在探讨快速霍夫变换(FHT)在车牌识别中的应用潜力。首先利用图像处理技术提取车牌字符,然后将FHT算法应用于图像中的每个字符进行识别和识别。本文使用的FHT算法是一种高效、快速、简单的字符识别算法,不需要较大的内存。
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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