Cg05_WaterEffect

本代码使用matlab实现理想高通滤波增强图像(Matlab to achieve ideal high-pass filtering to enhance the image)

禁用U的有一些小方法，用注册表和setupapi实现(Disabled U realize there are some small registry and setupapi)

说明：  《Visual c++ 项目开发案例 全程实录》（第二版）第11章 图像处理系统 配套源代码(&quot Visual c++ project development case full Record&quot (second edition) Chapter 11 of the image processing system supporting source code)

从Cbitmap派生的位图类，可通过指定一种颜色把一幅位图变透明，而它的使用差不多同Cbitamp一样简单。类中包含了两个文件：CISBitmap.cpp和CISBitmap.h，使用时附加进工程，可快速实现BMP位图图像的透明处理。(Cbitmap derived from the bitmap type, you can specify a color by a bitmap becomes transparent, and it s almost as simple as using the same Cbitamp. Class contains two files: CISBitmap.cpp and CISBitmap.h, into the use of additional works can be quickly processed to achieve a transparent bitmap BMP images.)

该程序是我多年的经验总结以及代码，实现了全景目标跟踪、火焰识别、烟雾识别、起立坐下行为判断、越界闯入、徘徊、违规停车等多种智能功能一体化，粒子滤波、贝叶斯分类器、随机森林等多种在线学习机制，还有传统的camshift、meanshift、光流法、卡尔曼滤波、struck、KCF、TLD、CT、区域匹配，相位相关、轮廓跟踪等多种算法(The program is my many years of experience and code, the realization of the panorama target tracking, flame detection, smoke detection, standing up sitting judge, cross-border intrusion, wandering, illegal parking and other various intelligent functions integration, particle filter, Bayesian classifier, random forest variety of online learning mechanism, and the traditional CAMSHIFT, meanshift, optical flow method, Kalman filter, the, KCF, regional matching, phase correlation, contour tracking and other several algorithms)

说明：  matlab实现的语音分析，其中，有lpc分析。程序都经过软件验证，没有错误。(matlab implementation of speech analysis, of which there lpc analysis. Software programs have been validated without error.)

编译原理实验，实现简单的正则表达式到nfa到dfa的过程。(compiler principle experiment, the realization of a simple regular expression to nfa to dfa process.)

本程序是关于TLD的多目标跟踪的程序，读取摄像头的图像，通过鼠标来框定多个目标，来实现对多个目标实时的跟踪和检测。

计算机网络选择重传协议，效率达到90 以上，北邮计科计算机网络课程作业(Select the computer network retransmission agreement, more than 90 efficiency, BUPT Jike computer network course work)

神经网络C程序的第3章(neural network C procedures for the Chapter 3)