基于区域统计和BP神经网络的车牌识别
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TP391.41

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License plate recognition based on regional statistics and BP neural network
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    摘要:

    为从车牌图像中获得车牌的字符信息,需要对字符识别系统进行研究。车牌识别过程分为图像预处理、车牌定位、车牌校正与分割和车牌字符识别4个环节。针对前3个环节,完成了图像中值滤波、Sobel算子边缘检测、数学形态学处理、Otsu二值化和Hough变换校正等工作,获得了单一标准字符图像。在车牌字符识别环节中,首先根据汉字位置,利用模板匹配算法对汉字进行识别,对于数字、字母字符,将字符图像分割,通过统计图像各部分的连通区域数以获得字符形态特征,据此设计并训练BP神经网络识别字符。最终获得能完成图像中的车牌字符识别的系统。

    Abstract:

    In order to obtain the character information of the license plate from the license plate image, it is necessary to study the character recognition system. The license plate recognition process is divided into four parts: image preprocessing, license plate location, license plate correction and segmentation, and license plate character recognition. For the first three links, image median filtering, Sobel operator edge detection, mathematical morphology processing, Otsu binarization and Hough transform correction were completed, and a single standard character image was obtained. In the license plate character recognition link, firstly, according to the position of Chinese characters, the template matching algorithm is used to identify Chinese characters. For digital and alphabetic characters, the character images are segmented, and the number of connected regions of each part of the image is obtained to obtain character shape features. And training BP neural network to recognize characters. Finally, a system that can complete the recognition of the license plate characters in the image is obtained.

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盛兆亮,高军伟.基于区域统计和BP神经网络的车牌识别[J].电子测量技术,2019,42(8):78-82

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  • 在线发布日期: 2021-08-16
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