用VB编写的完整的CAD程序，源代码提供，可以借鉴开发自己的CAD版本，一点遗憾的是说明是法语...

在中小型电力行业系统中，曲线的要求比较严格，虽然网络上面各种曲线控件非常多，但是很多只能提供一段时间的曲线显示或者历史若干个点的显示。比如在一个普通的小型水电站系统中我们会牵涉到许多的点（可能甚至达到400到500多个），一般的电站运行人员或者管理者希望能够对这类点的历史运行状况进行还原（即能够将历史运行的各个点状况进行还原），曲线就是非常重要的一个环节了 -SMEs in the power industry system, the curve of more stringent requirements, While the Network Control curve above all very, but many can only provide for a period of time curve or historical point of a number of shows. For example, in an ordinary small hydropower system, which will involve many of the points (which may even reach 4-500 many), Utility general operating personnel or managers hope to be able to point to the history of such operations conducted reduction (that is, to history Operation of each of the state reduction), the curve is a very important link in the

一个完整简单的PYTHON图像处理程序_1-a simple PYTHON has made a complete image-processing program _

介绍一种用VC实现的字符识别的方法,采用的是神经网络的算法-Introduce a character recognition method used VC, this method adopt NN Arithmetic.

图像的相关系数是衡量两幅图像的相关程度的，本代码直接通过选定区域计算出相关系数！-image correlation coefficient is a measure of two images of the code directly through selected regional correlation coefficient calculated!

sufer图象广泛应用于各行各业,本程序原代码,汇集了vc调用surfer指令的各种实例-sufer images are widely used in all walks of life, the program source code, a collection of command vc call surfer various examples of

这个源程序是一个显示三维模型的，功能是打开三维模型，然后可以对其进行旋转，平移等-this source is a three-dimensional model shows that its function is to open the three-dimensional model, which can then be its rotation, translation, etc.

一个可以椭圆或长方形作任意角度的的旋转的程序-an oval or rectangular can make arbitrary angle of the rotating procedures

个人搜集的两个大津法阈值分割算法(otsu算法)，已通过测试-personal collection of two large Zimbabwe law thresholding segmentation algorithm (Otsu algorithm), have passed the test

基于c++BuildER的图像的各角度的旋转-Based on c++ BuildER image of the angle of rotation

对图像进行逐点计算，并且取最大值和最小值的差值作为该点新的灰度值。 在区别边缘点和非边缘点时，首先确定一个阈值T，若图像中像素点的新 值大于该门限值，则可以初步确定为边缘点，小于T的新值被判断为非边缘点.-Image point by point basis, and taking the maximum and minimum points of difference as the new gray value. Edge in the difference between point and non-edge point, first determine a threshold T, if the image of the new pixel value is greater than the threshold, you can initially identified as the edge point, the new value is less than T have been judged as non-edge point.