目前该手写体识别系统主要分为 预处理模块： 主要包括训练数据和识别数据的读取，归一化，二值化 特征提取模块：主要包括笔划方向特征和网格密度特征，还可以根据对识别率的要求继续增加其他特征 识别（分类器）模块：主要包括SVM方法和BP神经网络的方法，其中SVM方法的识别率较高，SVM＋网格密度特征， 在小字符集情况下，达到了识别率97％以上 采用OO思想编写，适合做二次开发-currently the handwriting recognition system consists of pretreatment modules : including training data and identification data read, in one, two values of feature extraction module : the main characteristics of the direction including strokes and grid density characteristics, but also based on the identification of the requirements to continue to increase other identification ( Categories) modules : include SVM methods and BP networks, which SVM method for the identification of high SVM + mesh density characteristics, in a small set of characters to achieve a recognition rate of over 97% using OO ideological preparation, suitable for secondary development