基于Matlab的车牌定位及分割技术的研究与实现

发布时间：2018-06-25 15:06

  本文选题：车牌定位 + 多特征与多方法　； 参考：《西安电子科技大学》2014年硕士论文

【摘要】：伴随着科学技术的飞速发展、日常生活质量的全面提高，，汽车的数量在各个国家的总体数量都出现出了快速的增长。目前我国的汽车数量已经增加到一亿两千万辆，是世界汽车总数量的12%，已经成为了世界上第二大的汽车国家，并且其数量仍然在快速的增长当中。当然，随着汽车数量的不断增多，马路的不断加宽加长，对这些汽车的管理也就是现在的交通问题越来越被人们所关注，从而使其成为了一门很重要的学科来研究。在这门学科中主要研究的问题又依赖于对车辆的识别，车辆识别也就是车牌的识别。 一般车牌识别的步骤主要有三部分内容：车牌定位，车牌字符分割，车牌字符识别。这三个部分组成了一个完整的车牌识别的过程。由于精力有限，本文只对三个步骤中的车牌定位和字符分割进行相应的仿真研究。 本文用到的定位方法是根据车牌的字符本身的横向和纵向扫面特征、车牌的字符和底板的色彩差别特征，再结合其他的特征，通过特定算法的筛选过程来确定车牌位置并提取出车牌图像。主要算法是通过比较决定使用Prewitt算子边缘检测提取车牌的边缘信息，根据车牌的垂直方向扫面特征和周边色彩区别特点去除一定的干扰边缘信息，连接边缘点，标记连通域，根据车牌的形状特征并采用Adaboost方法继续去除干扰信息凸显车牌信息以分离出车牌图像，对分离出来的车牌图像倾斜校正，去除上下边界与左右边界得到精确的车牌字符区域。经过仿真分析，本文算法能够很好的定位出车牌图像，对单车牌图像和多车牌图像都适用，定位成功率高，通用性好。 本文的另外一部分是车牌分割，这部分内容第一步先分析了几种典型的字符分割的方法，使用了基于车牌垂直方向投影法与先验知识作为模板匹配结合的车牌字符分割方法来将前面经过精确定位的车牌字符图片分割成单独的字符。
[Abstract]:With the rapid development of science and technology, the overall improvement of the quality of daily life, the number of cars has increased rapidly in the total number of countries. At present, the number of cars in our country has increased to one hundred and twenty million vehicles, 12% of the total number of cars in the world, and has become the second largest automobile country in the world, and the number of cars in the world has become the second largest car country in the world. The number is still growing rapidly. Of course, with the increasing number of cars and the widening of the road, the management of these cars is becoming more and more concerned about the current traffic problems, which makes it a very important subject to study. Vehicle recognition and vehicle recognition are license plate recognition.
There are three main steps in the general license plate recognition: license plate location, license plate character segmentation, and license plate character recognition. These three parts make up a complete process of license plate recognition. Because of the limited energy, this paper only carries out the corresponding simulation research on the license plate location and character segmentation in the three steps.
The location method used in this paper is based on the characteristics of the transverse and longitudinal sweep of the character of the license plate, the characteristics of the color difference between the character of the license plate and the floor, and then combining the other features, the location of the license plate is determined by the selection process of the specific algorithm and the license plate image is extracted. The main calculation method is to determine the edge detection using the Prewitt operator by comparison. The edge information of the license plate is extracted, the interference edge information is removed according to the characteristics of the vertical sweep surface and the peripheral color, the edge points are connected and the connected domain is tagged. According to the shape feature of the license plate and the Adaboost method, the vehicle license information can be removed to separate the license plate image. The license plate image is inclined to correct, and the accurate license plate character area is obtained by removing the upper and lower boundary and the left and right boundaries. After simulation analysis, this algorithm can locate the license plate image well. It is suitable for both the single license plate image and the multiple license plate image, and the success rate of the location is high and the versatility is good.
The other part of this paper is the license plate segmentation. In this part, the first step is to analyze several typical character segmentation methods, and use the license plate character segmentation method based on the vertical direction projection method and the prior knowledge as template matching to divide the previously accurately located license plate character pictures into separate characters.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U495;TP391.41

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