随着经济的繁荣发展和人们消费水平的提高，汽车已经成为人们的必需品。随着

随着经济的繁荣发展和人们消费水平的提高，汽车已经成为人们的必需品。随着车辆数量的增加和信息化时代的进步，对交通管制，特别是车辆信息化、智能化管理的需求越来越大，因此车牌识别对于现代智能交通管理非常重要。本文使用Matlab软件开发环境对车辆图像进行读取和图像灰度化，车牌分割，车牌定位，车牌字符分割和车牌字符识别等一系列图像处理技术来获取车牌识别结果。本设计中的难点是车牌的字符分割和车牌的字符识别，在分割车牌字符方面，首先要找到连续的文本块，然后根据长度决定是否分割。如果找到的连续文本块的长度大于阈值，那么就意味着这个文本块是可以分割的。在识别车牌字符方面，为了提高对车牌的识别正确度，本文采用的是BP神经网络算法。最后通过GUI设计界面显示车牌识别结果。

With the prosperity and development of economy and the improvement of people's consumption level, cars have become people's necessities. With the increase of the number of vehicles and the progress of the information age, there is an increasing demand for traffic control, especially vehicle information and intelligent management. Therefore, license plate recognition is very important for modern intelligent traffic management. This paper uses MATLAB software development environment to read and gray the vehicle image, license plate segmentation, license plate location, license plate character segmentation and license plate character recognition and a series of image processing technologies to obtain the license plate recognition results. The difficulty in this design is the character segmentation of license plate and the character recognition of license plate. In the segmentation of license plate characters, we must first find continuous text blocks, and then decide whether to segment according to the length. If the length of the found continuous text block is greater than the threshold, it means that the text block can be segmented. In the aspect of license plate character recognition, in order to improve the recognition accuracy of license plate, this paper adopts BP neural network algorithm. Finally, the license plate recognition results are displayed through the GUI design interface.

With the prosperity and development of economy and the improvement of people's consumption level, cars have become a necessity for people. With the increase of the number of vehicles and the progress of the information age, the demand for traffic control, especially the information and intelligent management of vehicles, is increasing, so license plate recognition is very important for modern intelligent traffic management. In this paper, Matlab software development environment is used to read the vehicle image and a series of image processing technologies such as image graying, license plate segmentation, license plate location, license plate character segmentation and license plate character recognition to obtain the license plate recognition results. The difficulty in this design is the license plate character segmentation and the license plate character recognition. In the aspect of license plate character segmentation, we should first find the continuous text block, and then decide whether to segment it according to the length. If the length of the found continuous text block is greater than the threshold, it means that this text block can be divided. In recognition of license plate characters, in order to improve the accuracy of license plate recognition, this paper adopts BP neural network algorithm. Finally, the license plate recognition results are displayed through the GUI design interface.