牌照字符识别
License plate character recognition
字符识别方法目前主要有基于模板匹配算法和基于人工神经网络算法。基于模板匹配算法首先将分割后的字符二值化,并将其尺寸大小缩放为字符数据库中模板的大小，然后与所有的模板进行匹配，最后选最佳匹配作为结果。基于人工神经元网络的算法有两种：一种是先对待识别字符进行特征提取，然后用所获得特征来训练神经网络分配器；另一种州苗木 保定通风管道 丝网立柱模具 尼龙输送带 保定防水 保定空压机 高碑店养老院方法是直接把待处理图像输入网络，由网络自动实现特征提取直至识别出结果。
At present, the methods of character recognition are mainly based on template matching algorithm and artificial neural network algorithm. Based on the template matching algorithm, firstly, the segmented character is binarized, and its size is scaled to the size of the template in the character database, then it is matched with all the templates, and finally the best matching is selected as the result. There are two kinds of algorithms based on artificial neural network: one is to extract the features of the characters to be recognized first, and then train the neural network allocator with the acquired features; the other is to input the image to be processed into the network directly, and then the network automatically realizes the feature extraction until the result is recognized.