【作者】 余磊；

【导师】 付永生；

【作者基本信息】 山东大学 ， 信号与信息处理， 2013， 硕士

【摘要】 随着我国经济的迅速发展,汽车数量日益增加,而车辆管理模式相对落后,甚至一些地区仍以人工管理为主,因此如何提高交通管理的效率尤为重要。随着智能交通系统(Intelligent Transportation System, ITS)的产生及发展,各种资源开始得以充分利用,交通运输系统也得以有序化、智能化的管理。作为ITS重要的技术支柱,车牌识别(License Plate Recognition, LPR)技术开始被大量研究和推广。鉴于当前该技术的发展现状,如何在复杂背景下实时精准地识别车牌成为模式识别领域的一个研究热点。车牌识别技术主要包括车牌定位算法、车牌字符分割算法以及字符识别算法。本文在详细研究这些经典算法的基础上,结合国内车牌的特点,加以创新并提出了一些新的算法。通过大量实验验证,与以往算法相比,新算法在识别速度和精度上都有了很大的提高。本文对车牌识别技术展开研究,主要有以下三方面的创新：1.分析常见的车牌结构特征,学习当前经典的车牌定位算法,在此基础上提出基于多边缘特征的车牌定位算法,其中运用了颜色降维的方法,最大限度地去除了无关的冗余颜色信息。实验结果表明,该算法能够快速、精确地定位车牌区域,且抗干扰性强。2.在定位后获取的三值车牌图像的基础上,运用Hough变换法对车牌进行倾斜校正,运用投影法对字符进行垂直分割。该方法实验效果好,鲁棒性强,能够去除铆钉等背景噪声的干扰。3.分析、比较现有的经典车牌字符识别方法,提出了基于sift模版匹配与BP神经网络相结合的方法,分别对汉字和数字(字母)进行识别。通过仿真分析,该方法保证识别精度的同时,提高了识别速度。更多还原

【Abstract】 With the rapid development of national economy, the quantity of automobile increases rapidly in our country. But vehicle management mode has not followed the step actually, even it is still controlled by manual management in some areas, so it is very important to improve the efficiency of traffic control. Along with the emergence and development of Intelligent Transportation System(ITS), all kinds of resources can be used more efficiently, and the intellectualized transportation system can be controlled in order. As an important part of ITS, License Plate Recognition(LPR) technology has been widely studied and applied. Given the current development status of the technology, how to recognize the plate character in greater accuracy and less time-consuming under complex background, and it has became a hotspot in pattern recognize research.LPR technology is mainly combined by some parts such as plate location, char split and char recognition etc. In this paper, based on the characteristics of the Chinese plate, we study some classical algorithms, then propose some more effective algorithms. Many experimental results indicated that compared with those existing algorithms, new method has been greatly improved in speed and accuracy.This paper studied LPR technology, the main innovation has three aspects as follows:1. Analyzed structural feature of common license plate, studied classical plate location algorithms, and proposed a method of license plate location based on multiple edge features in the end, it employed the method of color dimension reduction to minimize the redundant color information. Experiment showed that the plate area can be located quickly and accurately, and it also validated strong robustness.2. Based on3-value image obtained by plate location, we used method of Hough transform to rotate some license plates which were tilt, and used projection method to segment the string. The experiment results showed the good performance.3. Compared and analyzed those existing classical methods of character recognition, then presented the template matching algorithm based on sift feature extraction to recognize the Chinese character, proposed the method based on BP neural network to identify the letter and digit. The experimental performance showed that those methods has higher accuracy and velocity.更多还原