【作者】 崔江；

【导师】 王友仁；

【作者基本信息】 南京航空航天大学 ， 电力电子与电力传动， 2003， 硕士

【摘要】 为了推动智能交通系统的发展，本文研究了基于图像检测的车型识别和车牌识别方法。 论文首先研究了车辆类型的识别方法，利用图像差分、直方图处理和中值滤波等技术得到车辆的侧面图像，然后提取图像特征输入至BP神经网络进行识别；其次对车牌自动识别技术进行了详细的探讨，车牌图像处理步骤包括：车牌定位、车牌图像二值化、车牌图像对比度分析、字符分割、特征提取，采用了三组BP神经网络对车牌字符进行识别。 利用实际行驶车辆信息进行验证，结果表明所研究的车型和车牌识别方法是正确有效的。更多还原

【Abstract】 In order to promote the development of Intelligent Transportation System, this paper researches the methods of vehicle classification and number plate recognition based on image process.In the paper, vehicle classification technique is firstly discussed. Some technologies such as image frames difference, histogram processing and median filter are applied to realize vehicle classification recognition module, and features extracted from the vehicle lateral image are put into BP neural network, which can classify the vehicle. Vehicle number plate recognition module is also discussed in the paper. Number plate image process consists of following several steps: number plate location, image binarization, plate contrast analysis, plate characters segmentation, feature extraction and three kinds of neural networks are used to realize characters recognition.The methods proposed by the paper are used to process actual vehicle images and the experiments results show that these methods are right and effective.更多还原