数字图像处理的课程设计，装起来有些麻烦，见附带的文本文档，可以做一些简单的栅格图像处理，但结合摄影测量获得的同名像点可以进行三维观测...

Revoluntion IDL示例程序 Revolution IDL unleashes the power of the IDL Object Graphics architecture by providing a high- level graphical user interface that allows the user to visualize data in a variety of ways, changing properties, positioning objects in 3D, and much more. -Example Revoluntion IDL procedures Revolution IDL unleashes the power of the IDL Object Graphics architecture by providing a high-level graphical user interface that allows the user to visualize data in a variety of ways, changing properties, positioning objects in 3D, and much more.

本代码实现了在三维空间中的飞行等设计，三维空间物体种类较多，较好的实现了模拟效果。-the code achieved in the 3D space flight such as design, 3D space objects more categories. achieve a better simulation effects.

这是书上的关于在线签名鉴定的代码，希望对大家有帮助-This is the book on-line signature identification code, and they hope to help everyone

kmeans This directory contains code implementing the K-means algorithm. Source code may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS program accepts input consisting of vectors and calculates the given number of cluster centers using the K-means algorithm. Output is directed to the screen. Usage for KMEANS is: KMEANS SOURCEFILE The format of the source file is: NPat - Number of patterns (int) SizeVect - Size of vector (int) NClust - Number of cluster centers(int) vect[1,1] ... vect[1,SizeVect] - vector 1 (real) vect[2,1] ... vect[2,SizeVect] - vector 2 (real) . . . . . . vect[NPat,1] ... vect[NClust,SizeVector] - vector N (real) To compile: ICC KMEANS.CPP -kmeans This directory contains code implementing the K-means algorithm. Source code may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS program accepts input consisting of vectors and calculates the given number of cluster centers using the K-means algorithm. Outpu

自动绘制各种线的演示程序。-automatically draw various lines demonstration program.

将矢量字光珊化！-to vector-Alexandra of the word!

模仿windows画图的小软件-imitate the small windows drawing software

直线光栅化gfdsg-linear grating of gfdsg

使用说明                                   代码注释的很详尽第一步：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。

直方图均衡化，局部直方图均衡化，直方图匹配，中值滤波，-histgram equalization,histogram matching