使用说明



第一步：训练网络。使用训练样本进行训练。（此程序中也可以不训练，因为笔者已经将训练好的网络参数保存起来了，读者使用时可以直接识别）





第二步：识别。首先，打开图像（256色）；再次，进行归一化处理，点击“一次性处理”；最后，点击“R”或者使用菜单找到相应项来进行识别。识别的结果显示在屏幕上，同时也输出到文件result.txt中。



该系统的识别率一般情况下为90 。



此外，也可以单独对打开的图片一步一步进行图像预处理工作，但要注意，每一步工作只能执行一遍，而且要按顺序执行。

具体步骤为：“256色位图转为灰度图”－“灰度图二值化”－“去噪”－“倾斜校正”－“分割”－“标准化尺寸”－“紧缩重排”。



注意，待识别的图片要与win.dat和whi.dat位于同一目录，这两文件保存训练后网络的权值参数。





具体使用请参照书中说明。-Help



The first step: Training Network. Training in the use of training samples. (This process may or may not be trained because the training I have saved up a good network parameters, and readers can use to identify)





Step two: identification. First, open the image (256 colors)　again, normalized to, click on the "one-time deal"　Finally, click "R" or use the menu to find the corresponding item in the Department. Recognition results showed on the screen, as well as output to a file in result.txt.



Recognition rate of the system under normal circumstances was 90 .



In addition, you can open a separate picture of the image pre-processing step by step, but it must be noted that the implementation of each step can only work once, but according to the order of implementation.

Concrete steps as: "256-color bitmap to grayscale"- "grayscale binary"- "noise"- "tip-tilt correction"- "split"- "the standardization of size"- "tight rearrangement."



Note that picture to be