cc

里面涉及了线宽线型的设置，各种图形，还有画笔画刷设置选择，颜色设置等，代码非常齐全，还有编程的每一步都有截图和说明(Which involves the linewidth linear settings, a variety of graphics, and brush brush settings selection, color settings, the code is very complete, and programming of every step have screenshots and description)

说明：  能精确的提取数字图像的轮廓。不管图形的形状如何，都能达到预期的效果。并且能将边界的坐标输出到一个文件中，供使用者分析数据。(Able to extract precise contours of the digital image. Regardless of the shape of how graphics can achieve the desired effects. The coordinates of the border and is capable of output to a file, for users to analyze data.)

用openCV实现，用Camshift算法实现彩色目标跟踪(openCV,color object tracking usingCamshift)

说明：   vc代码,用于图像直方图均衡（以原始girl图像为测试图像） (vc code, for image histogram equalization (in the original girl image for the test images))

改程序就代码可以找出从不同角度或区间的两幅遥感影像的同名点(Change the program code can find it from different angles of the same name point or interval of two remote sensing images)

经典的斑块分析算法，计算Blob的源码，算法很好。(Classical plaque analysis algorithms to calculate Blob source code, algorithms very well.)

VapourSynth-BM3D-master BM3D算法的原创代码，运行速度超快，参考文献《Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering》(VapourSynth-BM3D-master BM3D original algorithm code, run super-fast, Reference " Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering" )

用大整数乘法来计算两个n位二进制数相乘(With large integer multiplication to calculate the multiplication of two n-bit binary number)

采用了Harrtraining和离子滤波算法实现了拥挤人群人头计数，非常有用。VC++和Opencv开发，采用Oepncv中的Harrtraining训练一个分类器即可运行(Human detection and tracking in high density crowds is an unsolved problem. Standard preprocessing techniques such as background modeling fail when most of the scene is in motion. We integrate human detection and tracking into a single framework, and in- troduce a conrmation-by-classication method to estimate condence in a tracked trajectory, track humans through occlusions, and eliminate false positive detections.)

图像处理的IPP库使用手册，包括每个函数的使用说明，以及参数的意义。(IPP library of image processing using the manual, including instructions for each function, as well as the significance of the parameters.)