一个新创的算法（复杂）

将一幅图像旋转任意角度，手动输入角度，通过调试-To an arbitrary image rotation angle, manually enter the angle, through the debug

这是个基于MATLAB的对图像边缘进行编码的代码，可以直接运行下，不过要自己修改参数-This is a MATLAB-based encoding of the image edge of the code can be run directly under, but to modify its own parameters

本程序可以在VC++6.0的环境下实现图象的还原功能，例如逆滤波-This procedure can VC++ 6.0 environment to achieve the reduction of image features, such as inverse filtering

When creating applications with a complex view layout, there are several features that are missing from MFC. First, each type of view layout is created differently (simple view vs. splitter vs. nested splitter). Simple view layout does not need any additional code (MFC handles the creation). Splitter layout needs a CSplitterWnd and manual creation of each pane. Even more complex is the nested splitter. Second, MFC does not support tab windows that can be found in almost any commercial application and is great for better UI orgranization.

数字识别，识别手写体。 使用神经网络算法编写。 识别率一般，带训练功能-Number recognizing system,used to recogize the hand writing figures.It is writen by nero network and has low recognizing effects but we can exercise it.

计算机图形学中用经典算法实现的绘图程序，包括直线生成、圆弧生成、线段裁剪、多边形裁剪等-Computer graphics with the classic algorithm of mapping procedures, including a straight-line generation, arc formation, line cutting, cutting, such as polygon

butterworth高通滤波，里面有两个巴特沃斯高通滤波函数，我试过了，都可以用。-butterworth high-pass filtering, there are two high-pass Butterworth filter function, I tried, you can use.

该系统是为了实现对一系列图片中运动物体的跟踪而设计的，它通过对一系列图片的处理， 提取出图片背景，识别出运动物体，进而对运动物体进行跟踪，得到运动物体的轨迹。 -the system is design for tracking objects in a series of images.First it extracts the backgroud of the picture through dealing with corresponding images. Then we can realize to track the motion object and get the trajectory of the object

图像颜色空间的转换_RGB -HSV，非常适合初学者作为例子学习。-image color space conversion _RGB-HSV, very suitable for beginners as an example to study.

是一个关于神经网络的仿真程序，用于提取特征参数后的图像识别-Is a study on the neural network simulation program, used to extract characteristic parameters of the image recognition