均值背景建模

算法原理

原理，，将所有帧的像素点相加，取平均作为背景的估计，其中N是当前所在帧，不是所有帧。

Matlab实现

mov=aviread('highway.AVI');      %读入
fnum=size(mov,2)               ; %读取电影的祯数，mov为1*temp
[x,y,z]=size(mov(1).cdata(:,:,:));
frame_src=zeros(x,y,z);       %原始图像
frame_all=zeros(x,y,z);  
frame_avg=zeros(x,y,z);       %平均图像
frame_src_avg=zeros(x,y,z);   %原始图像减平均图像
frame_src_avg_all=zeros(x,y,z); 
frame_result=zeros(x,y,z);
for i=1:fnum
    frame_src=mov(i).cdata(:,:,:);
    frame_src=double(frame_src);
    frame_all=frame_all+frame_src;
    frame_avg=frame_all/i;
%     frame_src_avg=sqrt(frame_src.^2-frame_avg.^2);
%     frame_src_avg_all=frame_src_avg_all+frame_src_avg;
%     frame_result=frame_src_avg/i;
    subplot(2,2,1);
    frame_src=uint8(frame_src);
    imshow(frame_src);
    title('原始图像');
    subplot(2,2,2);
    frame_avg=uint8(frame_avg);
    imshow(frame_avg);
    title('背景');
    
%     frame_src_gray=rgb2gray(frame_src);
%     frame_avg_gray=rgb2gray(frame_avg);
%     f=frame_src_gray-frame_avg_gray;
%     subplot(2,2,3);
%     imshow(f);
    pause(0.1);
end

实现效果

Opencv实现

#include "cv.h"
#include "cxcore.h"
#include "highgui.h"
#include <stdio.h>
#include<math.h>

#define image_width 320
#define image_height 240

int main(int argc,char** argv)
{
	int i;
	double alpha=0.0,beta=0.0;
	CvCapture* capture=cvCaptureFromAVI("E:\研二上\video\highway.AVI");
	if(!capture)
	{
		printf("Could not initialize...
");
		return -1;
	}
	IplImage* img=cvQueryFrame(capture);
	IplImage* background=cvCreateImage(cvSize(img->width,img->height),img->depth,3);
	IplImage* advbackground=cvCreateImage(cvSize(img->width,img->height),img->depth,3);
	int index=0;

	cvNamedWindow("video",1);
	cvNamedWindow("back",1);
	cvNamedWindow("advback",1);

	CvMat* Mat_src=cvCreateMat(img->height,img->width,CV_32FC3);
	CvMat* Mat_dst=cvCreateMat(img->height,img->width,CV_32FC3);
	CvMat* Mat_dst1=cvCreateMat(img->height,img->width,CV_32FC3);
	CvMat* Mat_tmp1=cvCreateMat(img->height,img->width,CV_32FC3);
	CvMat* Mat_tmp2=cvCreateMat(img->height,img->width,CV_32FC3);

	CvMat* Mat1 = cvCreateMat(img->height,img->width,CV_32FC3);
	CvMat* Mat2 = cvCreateMat(img->height,img->width,CV_32FC3);
	CvMat* Mat3 = cvCreateMat(img->height,img->width,CV_32FC3);
	CvMat* Mat4 = cvCreateMat(img->height,img->width,CV_32FC3);
	cvSetZero(Mat_dst);
	cvSetZero(Mat2);
	cvSetZero(Mat3);

	while(img=cvQueryFrame(capture)) 
	{
		index++;
		printf("index%d
",index);
		cvShowImage("video",img);
		cvConvert(img,Mat_src);                                    //转换成32位浮点型		
			cvAdd(Mat_src,Mat_dst,Mat_dst);
			for(i=0;i<(Mat_dst1->rows*Mat_dst1->cols*3);i++)
			{
				Mat_dst1->data.fl[i]=Mat_dst->data.fl[i]/index;
			}
				
			for(i=0;i<(Mat1->rows*Mat1->cols*3);i++)
			{
				Mat1->data.fl[i] = sqrt(pow(Mat_src->data.fl[i],2.0f)-pow(Mat_dst1->data.fl[i],2.0f));
			}
			cvAdd(Mat1,Mat2,Mat2);
			for(i=0;i<(Mat3->height*Mat3->width*3);i++)
			{
				Mat3->data.fl[i] = Mat2->data.fl[i]/index;                   //残影部分
			}
			for(i=0;i<(Mat4->height*Mat4->width*3);i++)
			{
				Mat4->data.fl[i] =abs(Mat_dst1->data.fl[i]-Mat3->data.fl[i]);   //改进后的阵列
			}
			cvConvert(Mat1,advbackground);
			cvShowImage("advback",advbackground);
		cvConvert(Mat_dst1,background);
		cvShowImage("back",background);
		cvWaitKey(50);
	}
	cvDestroyWindow("video");
	cvReleaseCapture( &capture );
	return 0;
}

实现效果