function

基于主像素的背景建模方法。该方法对密集目标检测效果较好。(Based on the background of the main pixel modeling method. The method of intensive better target detection.)

转辙机图像采集板区域参数设置上位机界面程序，转辙机通信协议，多项式拟合参数及阈值设置。(Switch machine image acquisition board area parameter set PC interface program, switch machine communication protocols, polynomial fitting parameters and the threshold value is set.)

对两幅图像进行配准，分别提取两幅图像的surf特征点以及描述子，得到粗匹配结果，然后根据粗匹配结果，采用ransac方法计算基础矩阵，并去除误匹配点，得到较准确匹配结果(Two image registration, surf was extracted from the feature points in two images to get the coarse matching and descriptor, then according to the results, the coarse matching results, using RANSAC method to calculate the fundamental matrix, and eliminate the error matching, gain a more accurate matching results)

直方图均衡化处理编程指南及实验报告，数字图像处理及应用，阮秋琦教授，北京交通大学（资源分享）。(Histogram equalization processing programming guide and laboratory reports，Application of digital image processing and Beijing Jiaotong University, Professor Ruan Qiuqi)

该上传的256张CT图片是高质量的DICOME格式人类头骨的连续序列切片图，可直接用于医学三维重建或体绘制。(The upload of 256 CT images are of high quality DICOME form a continuous sequence of the human skull slice diagram can be directly used in medical 3D reconstruction or volume rendering.)

多边形填充作业.rar(filled polygon operations. Rar)

说明：  在地震处理中，非常经典的进行时深转换的程序，通常比较好用(In seismic processing, the very classic procedure for time-depth conversion, usually more useful)

VC++图像平滑处理+程序源码，实现图象的平滑（去噪声），锐化功能，测试时请在C盘下放一个测试用的Bmp图片，路径：C: est.bmp，没有的话没法测试。如上图所示是水平平滑处理，可以对比下，不过感觉颜色失真了，有兴趣的看一下。命令行编译过程如下： 　　vcvars32 　　rc bmp.rc 　　cl smooth.c bmp.res user32.lib gdi32.lib(VC++ image smoothing+ program source code, to achieve a smooth image (to noise), sharpening function in the C drive when testing a test of decentralization Bmp picture, path: C: test.bmp, no words can not test . Is shown above the level of smoothing, you can compare the next, but the feeling of color distortion, interested look. Command-line compiler as follows: vcvars32 rc bmp.rc cl smooth.c bmp.res user32.lib gdi32.lib)

多尺度快速角点检测算法（FAST).Adaptive and generic corner detection based on the accelerated segment test. 出处 Computer Vision–ECCV 2010(Multi-scale fast corner detection algorithm (FAST) Adaptive and generic corner detection based on the accelerated segment test. Computer Vision-ECCV 2010)

针对opencv的配制方法总结，适合初学者来配置开发环境(For the preparation of opencv summary, suitable for beginners to configure the development environment)