opencv混合高斯模型

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基于混合高斯模型，对运动背景下的背景进行建模学习，其中运动物体可以较好的判断

#include <stdio.h>#include <cv.h>#include <cxcore.h>#include <highgui.h>#include <cvaux.h>//必须引此头文件#include <iostream>#include <string>#include <opencv2/opencv.hpp>using namespace std;using namespace cv;int main(int argc, char** argv){ string videoFile = "test3.avi"; VideoCapture capture; capture.open(videoFile); if (!capture.isOpened()) {  cout<<"read video failure"<<endl;  return -1; } BackgroundSubtractorMOG2 mog; Mat foreground; Mat background; Mat frame; long frameNo = 0; while (capture.read(frame)) {  ++frameNo;  cout<<frameNo<<endl;  // 运动前景检测，并更新背景  mog(frame, foreground, 0.001);        // 腐蚀  erode(foreground, foreground, Mat());// 膨胀  dilate(foreground, foreground, Mat());   mog.getBackgroundImage(background);  // 返回当前背景图像    imshow("高斯模型前景", foreground);  imshow("高斯模型背景", background);////  //当前帧与背景图像差分////  Mat sub1=frame-background;////  Mat sub2=background-frame;////  Mat sub=sub1+sub2;//////////  Mat sub=(sub3+foreground);////  IplImage subimage=sub;////  //cvCvtColor(&subimage,&subimage,CV_BGR2GRAY);//// //imshow("chafen",sub);////  //// cvSaveImage("subimage.jpg",&subimage);//// IplImage* subjpg = cvLoadImage("subimage.jpg");//// IplImage*  psubImg = cvCreateImage(cvSize(subjpg->width, subjpg->height),  IPL_DEPTH_8U,1);////CvMat* psubMat = cvCreateMat(subjpg->height, subjpg->width, CV_32FC1);////cvCvtColor(subjpg,psubImg,CV_BGR2GRAY);////cvConvert(psubImg, psubMat);//////二值化前景图////cvThreshold(psubMat, psubImg, 15, 255.0, CV_THRESH_BINARY);////cvErode(psubImg, psubImg, 0, 1);////cvDilate(psubImg, psubImg, 0, 1);////cvShowImage("背景差分法前景目标",psubImg);  if (waitKey(25) > 0)  {   break;  } }  return 0;}

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