opencv混合高斯模型

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;
}