核心代码关于vibe算法的有用部分

一vibe.cpp// vibe.cpp : Defines the entry point for the console application.//// lx_Picture.cpp : Defines the entry point for the console application. //#include"stdafx.h"#include"cv.h"//#include <opencv2/opencv.hpp>#include"highgui.h"#include"hanshu.h"#include<iostream>using namespace std;using namespace cv;int nFrmNum = 0;//记录帧数int Width;//记录帧的宽度int Height;//记录帧的高度int FrameRate;//记录视频帧率#define zero 1e-12#define DIS(a,b) sqrt(double((a.x-b.x)*(a.x-b.x)+(a.y-b.y)*(a.y-b.y))) #define SGN(x) (fabs((double) x)<zero?0:(x>0?1:-1))#define CROSS(a,b,c) ((b.x-a.x)*(c.y-a.y)-(b.y-a.y)*(c.x-a.x))//叉积，用来判断旋转方向#define CMP(a,b) (a.x<b.x||SGN(a.x-b.x)==0 &&a.y<b.y)//坐标的比较#define RAND (rand()%100000/100000.0)//产生-1之间的浮点数IplImage *img;//IplImage *imgRGB;IplImage *imggray;IplImage *imgmat;IplImage* pFrameb;int hull_size = 0;//CvPoint* hull_p;void draw_hull(CvPoint *pm,int pointnum);inline void swap(CvPoint p[],int x,int y);inline void push(CvPoint*S,CvPoint pt);inline CvPoint pop(CvPoint*S);void sort(CvPoint p[],int l,int r);void Resultprocess(IplImage *pimg);int main(int argc, char* argv[]){IplImage* pFrame=NULL;CvMat* pFrameMat = NULL;//pFrame对象IplImage* pAfter=NULL;CvMat* pAfterMat=NULL;//保存pFrame对应的灰度图像IplImage* segMap=NULL;CvMat* segMat=NULL;//保存处理后的信息IplImage* pFrameSeg;//2013.8.24IplImage* redImage=NULL;IplImage* greenImage=NULL;IplImage* blueImage=NULL;pFrameb=NULL;IplImage* pFrMatImg=NULL;////2013.8.24IplImage *segMapbg=NULL; //保存图像和后处理用IplImage *segMapdif=NULL; //保存图像和后处理用IplImage* pFramec;//要读取的视频文件和保存的视频文件路径char* openfile="F:\\Users\\win\\Desktop\\west5_2.avi";char* outfile="F:\\Users\\win\\Desktop\\vibe.avi";char filename[100];//保存的图像位置和名称//打开视频文件CvCapture* pCapture=cvCreateFileCapture(openfile);if(pCapture==NULL) {cout<<"video file open error!"<<endl;return -1;}//获取视频相关信息，帧率和大小double fps=cvGetCaptureProperty(pCapture,CV_CAP_PROP_FPS);CvSize size=cvSize((int)cvGetCaptureProperty(pCapture,CV_CAP_PROP_FRAME_WIDTH)*2, (int)cvGetCaptureProperty(pCapture,CV_CAP_PROP_FRAME_HEIGHT));//创建输出视频文件CvVideoWriter* Save_result=NULL;Save_result=cvCreateVideoWriter(outfile,CV_FOURCC('X','V','I','D'),fps,size,1);IplImage* dstImg=cvCreateImage(size,IPL_DEPTH_8U,3);//创建要保存的图像//创建窗口cvNamedWindow("video",CV_WINDOW_AUTOSIZE);//0.25//cvNamedWindow("debug",1);//2013.8.28//创建一个随机数生成器RNG rng(0xFFFFFFFF);//定义字体CvFont font;cvInitFont( &font, CV_FONT_HERSHEY_COMPLEX_SMALL ,1, 1, 0, 1, 8);//逐帧读取视频并进行处理while(pFrame = cvQueryFrame( pCapture )){nFrmNum++;//如果是第一帧，申请内存并进行初始化if(nFrmNum==1){segMap = cvCreateImage(cvSize(pFrame->width, pFrame->height),IPL_DEPTH_8U,1);segMat = cvCreateMat(pFrame->height, pFrame->width, CV_32FC1);pAfter=cvCreateImage(cvSize(pFrame->width, pFrame->height),IPL_DEPTH_8U,1);pAfterMat=cvCreateMat(pFrame->height, pFrame->width, CV_32FC1);//2013.8.24redImage=cvCreateImage(cvSize(pFrame->width,pFrame->height),IPL_DEPTH_8U,1);//用于存储输入图像的红色分量图像greenImage=cvCreateImage(cvSize(pFrame->width,pFrame->height),IPL_DEPTH_8U,1);//用于存储输入图像的绿色分量图像blueImage=cvCreateImage(cvSize(pFrame->width,pFrame->height),IPL_DEPTH_8U,1);//用于存储输入图像的蓝色分量图像pFrameb = cvCreateImage(cvSize(pFrame->width, pFrame->height),IPL_DEPTH_8U,3);pFramec = cvCreateImage(cvSize(pFrame->width, pFrame->height),IPL_DEPTH_8U,3);//保存图像用pFrMatImg = cvCreateImage(cvSize(pFrame->width, pFrame->height), IPL_DEPTH_8U,1);//空洞填充img=cvCreateImage(cvSize(pFrame->width,pFrame->height),IPL_DEPTH_8U,3);imggray=cvCreateImage(cvSize(pFrame->width,pFrame->height),IPL_DEPTH_8U,1);imgmat=cvCreateImage(cvSize(pFrame->width,pFrame->height),IPL_DEPTH_8U,1);cvCopy(pFrame, pFrameb,0);//2013.9.13cvCopy(pFrame, pFramec,0);//2013.9.23//滤波//中值滤波，去掉噪声//cvSmooth(pFrame, pFrameb, CV_MEDIAN, 3, 0, 0,0);////均衡化处理，克服亮度影响.2.11//cvSplit(pFrameb,blueImage,greenImage,redImage,NULL);//将彩色图像pFrame 的蓝色分量图像blueImage﹑绿色分量图像greenImage和红色分量图像redImage提取出来//cvEqualizeHist(redImage,redImage);//对红色分量图像进行直方图均衡化处理//cvEqualizeHist(greenImage,greenImage); //对绿色分量图像进行直方图均衡化处理//cvEqualizeHist(blueImage,blueImage); //对蓝色分量图像进行直方图均衡化处理//cvMerge(blueImage,greenImage,redImage,NULL,pFrameb);//将经过直方图均衡化的蓝色﹑绿色﹑红色图像合并成彩色图像,存储在pFrameb中//cvCopy(pFrameb,pFrame,0);////2013.8.24segMapbg = cvCreateImage(cvSize(pFrame->width, pFrame->height),IPL_DEPTH_8U,1); //2013.8.28segMapdif = cvCreateImage(cvSize(pFrame->width, pFrame->height),IPL_DEPTH_8U,1); //2013.8.28pFrameSeg=cvCreateImage(cvSize(pFrame->width, pFrame->height),IPL_DEPTH_8U,3);//转化成单通道图像再处理cvCvtColor(pFrame, pAfter, CV_BGR2GRAY);cvConvert(pAfter, pAfterMat);Initialize(pAfterMat,rng);}else {//2013.8.24//滤波//中值滤波，去掉噪声//cvSmooth(pFrame, pFrameb, CV_MEDIAN, 3, 0, 0,0);////均衡化处理，克服亮度影响.2.11//cvSplit(pFrameb,blueImage,greenImage,redImage,NULL);//将彩色图像pFrame 的蓝色分量图像blueImage﹑绿色分量图像greenImage和红色分量图像redImage提取出来//cvEqualizeHist(redImage,redImage);//对红色分量图像进行直方图均衡化处理////cvEqualizeHist(greenImage,greenImage); //对绿色分量图像进行直方图均衡化处理////cvShowImage("debug",greenImage);//cvEqualizeHist(blueImage,blueImage); //对蓝色分量图像进行直方图均衡化处理////cvMerge(blueImage,greenImage,redImage,NULL,pFrameb);//将经过直方图均衡化的蓝色﹑绿色﹑红色图像合并成彩色图像,存储在pFrameb中//cvCopy(pFrameb,pFrame,0);////2013.8.24cvCopy(pFrame, pFrameb,0);//2013.9.13cvCopy(pFrame, pFramec,0);//2013.9.23cvCvtColor(pFrame,pAfter,CV_BGR2GRAY);cvConvert(pAfter,pAfterMat);update(pAfterMat,segMat,rng,nFrmNum);//更新背景cvConvert(segMat,segMap);//进行形态学滤波，去掉噪音2013.8.24cvErode(segMap, segMap, 0, 1);cvDilate(segMap, segMap, 0, 1);//cvSmooth(segMap, segMap, CV_MEDIAN, 3, 0, 0,0);//掩膜空洞填充//将大背景全部用前景色（白色）填充cvCopy(segMap,pFrMatImg,0);CvPoint seedPoint=cvPoint(0,0);cvFloodFill(pFrMatImg,seedPoint,cvScalarAll(255),cvScalarAll(0),cvScalarAll(0),NULL,8,NU LL);//取反.2.1cvNot(pFrMatImg,pFrMatImg);//与原二值图像相加cvAdd(segMap,pFrMatImg,segMap,0);//cvShowImage("debug",segMap);cvCvtColor(segMap,pFrameSeg,CV_GRAY2BGR);// 下面的程序段用来找到轮廓去除小块CvSeq *cont;CvMemStorage *stor;// Create dynamic structure and sequence.stor = cvCreateMemStorage(0);cont = cvCreateSeq(CV_SEQ_ELTYPE_POINT, sizeof(CvSeq), sizeof(CvPoint) , stor);//找到所有轮廓cvFindContours( segMap, stor, &cont, sizeof(CvContour),CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0));// 直接使用CONTOUR中的矩形来处理for(;cont;cont = cont->h_next){CvRect r = ((CvContour*)cont)->rect;// if(r.height * r.width >16) // 面积大的方形保留// {// //对轮廓连通域进行颜色填充：//// cvRectangle( imggray, cvPoint(r.x,r.y), cvPoint(r.x + r.width, r.y + r.height),CV_RGB(255,255,255), CV_FILLED, 8,0);// }if(r.height * r.width < 16) // 面积小的方形抛弃掉{//对轮廓连通域进行颜色填充：cvRectangle( segMap, cvPoint(r.x,r.y), cvPoint(r.x +r.width, r.y + r.height),CV_RGB(0,0,0), CV_FILLED, 8,0);}}//2013.8.24if (nFrmNum==2){cvCopy(segMap,segMapbg);}//2013.8.28//将segMap转换成三通道图像存在pFrame中cvCvtColor(segMap,pFrame,CV_GRAY2BGR);//去掉时间显示数字变化的影响2013.9.9int i;int j;for (i=pFrame->height/18;i<pFrame->height/8;i++ ){for (j=pFrame->width/7;j<pFrame->width/4;j++){(pFrame->imageData+i*pFrame->widthStep)[3*j]=0;(pFrame->imageData+i*pFrame->widthStep)[3*j+1]=0;(pFrame->imageData+i*pFrame->widthStep)[3*j+2]=0;}}//后处理，只有有运动物体才需要//当前帧跟背景图相减cvAbsDiff(segMap, segMapbg, segMapdif);//二值化前景图cvThreshold(segMapdif,segMapdif, 25, 255.0, CV_THRESH_BINARY);/*cvShowImage("debug",segMapbg);*/CvScalar avgsum;avgsum=cvAvg(segMapdif,NULL);double avgvalue=avgsum.val[0]+avgsum.val[1]+avgsum.val[2]+avgsum.val[3];double pixelnum=pFrame->width*pFrame->height;if (avgvalue >= 4000/pixelnum){Resultprocess(pFrame);cvCvtColor(imggray,pFrame,CV_GRAY2BGR);// 找到所有轮廓cvFindContours( imggray, stor, &cont, sizeof(CvContour),CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE,cvPoint(0,0));// 直接使用CONTOUR中的矩形来画轮廓for(;cont;cont = cont->h_next){CvRect r = ((CvContour*)cont)->rect;cvRectangle( pFrameb, cvPoint(r.x,r.y), cvPoint(r.x + r.width, r.y + r.height),CV_RGB(255,255,255), 1, 8,0);}}// free memorycvReleaseMemStorage(&stor);//载入原图像到目标图像cvSetImageROI(dstImg, cvRect(0, 0, pFrame->width, pFrame->height));cvCopy(pFrameb, dstImg);cvResetImageROI(dstImg);//载入检测后的图像到目标图像cvSetImageROI(dstImg, cvRect(pFrame->width, 0, pFrame->width*2, pFrame->height));// cvCopy(pFrame, dstImg);cvCopy(pFrameSeg, dstImg);cvResetImageROI(dstImg);//显示提示文字cvPutText(dstImg, "Origin Video", cvPoint(0,pFrame->height-8),&font,CV_RGB(255,255,0));cvPutText(dstImg, "Foreground Video",cvPoint(pFrame->width,pFrame->height-8),&font,CV_RGB(255,255,0));//保存视频和输出cvWriteFrame(Save_result,dstImg);//输出图片,有物体才保存//当前帧跟背景图相减//cvAbsDiff(segMap, segMapbg, segMapdif);////二值化前景图//cvThreshold(segMapdif,segMapdif, 25, 255.0, CV_THRESH_BINARY);///*cvShowImage("debug",segMapbg);*/// CvScalar avgsum;//avgsum=cvAvg(segMapdif,NULL);//doubleavgvalue=avgsum.val[0]+avgsum.val[1]+avgsum.val[2]+avgsum.val[3];//double pixelnum=pFrame->width*pFrame->height;// if (avgvalue >= 4000/pixelnum)// {//if(nFrmNum<11)//sprintf(filename,"E:\\cjr\\Programs\\programs\\Vibe_zx\\pictureRGB\\000%d_Vibe.jpg",nFrm Num-1); //pictureRGB//else if(nFrmNum<101)//sprintf(filename,"E:\\cjr\\Programs\\programs\\Vibe_zx\\pictureRGB\\00%d_Vibe.jpg",nFrmN um-1);//else if(nFrmNum<1001)//sprintf(filename,"E:\\cjr\\Programs\\programs\\Vibe_zx\\pictureRGB\\0%d_Vibe.jpg",nFrmNu m-1);//else if(nFrmNum<10001)//sprintf(filename,"E:\\cjr\\Programs\\programs\\Vibe_zx\\pictureRGB\\%d_Vibe.jpg",nFrmNum -1);//cvSaveImage(filename,pFramec);//pFrameSeg// }cvShowImage("video",dstImg);if(cvWaitKey(5)>=0) break;}}cvReleaseImage(&pFrame);cvReleaseMat(&pFrameMat);cvReleaseImage(&pAfter);cvReleaseMat(&pAfterMat);cvReleaseImage(&segMap);cvReleaseMat(&segMat);cvReleaseVideoWriter(&Save_result);cvReleaseImage(&dstImg);cvDestroyWindow("video");//2013.8.24cvReleaseImage(&redImage);cvReleaseImage(&greenImage);cvReleaseImage(&blueImage);cvReleaseImage(&pFrameb);cvReleaseImage(&pFramec);cvReleaseImage(&pFrMatImg);//2013.8.24cvReleaseImage(&img);cvReleaseImage(&imggray);cvReleaseImage(&imgmat);cvDestroyWindow("Image");return 0;}void Resultprocess(IplImage *pimg){int fgpixelnum=0;uchar *fgimagdata;// cvNamedWindow("ImageProcess");// cvNamedWindow("Image");cvCopy(pimg,img);cvCvtColor(img,imggray,CV_RGB2GRAY);//提取轮廓cvCanny(imggray,imggray,5,40,3);// cvShowImage("Image",imggray);// cvWaitKey(0);CvPoint *pz = NULL;pz=new CvPoint[img->width*img->height];CvPoint *ptmp= pz;//统计前景像素数fgimagdata=(uchar*)imggray->imageData;int step=(imggray->widthStep/(sizeof(uchar)));double fgimgvalue =0;for (int i=0; i<imggray->height; i++){for (int j=0; j<imggray->width;j++){fgimgvalue=fgimagdata[step*i+j];if (fgimgvalue>10){fgpixelnum++;pz->x=j;pz->y=i;pz++;}}}pz=ptmp;draw_hull(pz,fgpixelnum);pz=ptmp;//free(pz);delete pz;return;}void draw_hull( CvPoint *pm,int pointnum){int min=-1;CvPoint* hull_p = new CvPoint[ pointnum];//用来储存凸包上的点CvPoint *p;//=(CvPoint*)malloc(sizeof(CvPoint)*(img->width*img->height));/* CvPoint *ptp;ptp=p;*/p=pm;//找出x坐标最小的,作为起始点//for(int j=0;j<pointnum;j++){if ( min == -1 || CMP( p[j],p[min])){min = j;}}if(min!=0)swap(p,0,min);sort(p,1,pointnum-1);//其他点排序push(hull_p,p[0]);push(hull_p,p[1]);push(hull_p,p[2]);for(int i=3;i<pointnum-1;i++) //pointnum-1?{while(CROSS(hull_p[hull_size-2],hull_p[hull_size-1],p[i])<0)//非左转{pop(hull_p);//cvLine(imggray,hull_p[hull_size-1],p[i],cvScalar(255,0,255));//为了看清运行过程而加的//cvShowImage("ImageProcess",imggray);//cvWaitKey(100);}//cvLine(imggray,hull_p[hull_size-1],p[i],cvScalar(255,0,255));push(hull_p,p[i]);}cvPolyLine(imggray,&hull_p,&hull_size,1,1,cvScalar(255,255,255),2);//最终画出凸包//填充//掩膜空洞填充//将大背景全部用前景色（白色）填充cvCopy(imggray,imgmat,0);CvPoint seedPoint=cvPoint(0,0);cvFloodFill(imgmat,seedPoint,cvScalarAll(255),cvScalarAll(0),cvScalarAll(0),NULL,8,NULL) ;//取反.2.1cvNot(imgmat,imgmat);//与原二值图像相加cvAdd(imggray,imgmat,imggray,0);free(hull_p);hull_size=0;/*p=ptp;free(p);*/}//下面简单实现了栈操作inline void push(CvPoint*S,CvPoint pt){S[hull_size++]=pt;}inline CvPoint pop(CvPoint*S){return S[--hull_size];}inline void swap(CvPoint p[],int x,int y){CvPoint pt = p[x];p[x] = p[y];p[y]=pt;}inline bool compare(CvPoint a,CvPoint b,CvPoint c) {//int tmp = SGN(double( CROSS(a,b,c)));if(tmp!=0)return tmp>0;//如果两点共线的话,就需要比较远近了//elsereturn DIS(a,b)< DIS(a,b);}//快排，极角的排序void sort(CvPoint p[],int l,int r){CvPoint tmp = p[(l+r)/2];int i = l;int j = r;do{while(compare(p[0],p[i],tmp))i++;while(compare(p[0],tmp,p[j]))j--;if(i <= j){swap(p,i,j);i++;j--;}}while(i<=j);if(i<r)sort(p,i,r);if(j>l)sort(p,l,j);}二huangshu.cpp#include"stdafx.h"#include"hanshu.h"#include"cv.h"//#include <opencv2/opencv.hpp>#include"highgui.h"#include<math.h>#include<iostream>using namespace std;using namespace cv;static int c_xoff[9] = {-1, 0, 1, -1, 1, -1, 0, 1, 0};//x的邻居点static int c_yoff[9] = {-1, 0, 1, -1, 1, -1, 0, 1, 0};//y的邻居点float samples[1024][1024][defaultNbSamples+1];//保存每个像素点的样本值//初始化void Initialize(CvMat* pFrameMat,RNG rng){//记录随机生成的行(r) 和列(c)int rand,r,c;//对每个像素样本进行初始化for(int y=0;y<pFrameMat->rows;y++){//Heightfor(int x=0;x<pFrameMat->cols; x++){//Widthfor(int k=0;k<defaultNbSamples;k++){//随机获取像素样本值rand=rng.uniform( 0, 9 );r=y+c_yoff[rand]; if(r<0) r=0; if(r>=pFrameMat->rows) r=pFrameMat->rows-1; //行c=x+c_xoff[rand]; if(c<0) c=0; if(c>=pFrameMat->cols) c=pFrameMat->cols-1; //列//存储像素样本值samples[y][x][k]=CV_MAT_ELEM(*pFrameMat,float,r,c); //CV_MAT_ELEM opencv中用来访问矩阵每个元素的宏，这个宏只对单通道矩阵有效}samples[y][x][defaultNbSamples]=0;}}}//更新函数void update(CvMat* pFrameMat,CvMat* segMat,RNG rng,int nFrmNum){for(int y=0;y<pFrameMat->rows;y++){ //Heightfor(int x=0;x<pFrameMat->cols;x++){ //Width//用于判断一个点是否是背景点,index记录已比较的样本个数，count表示匹配的样本个数int count=0,index=0;float dist=0;//while((count<defaultReqMatches) && (index<defaultNbSamples)){dist=CV_MAT_ELEM(*pFrameMat,float,y,x)-samples[y][x][index];if(dist<0) dist=-dist;if(dist<defaultRadius) count++;index++;}if(count>=defaultReqMatches){//判断为背景像素,只有背景点才能被用来传播和更新存储样本值samples[y][x][defaultNbSamples]=0;*((float *)CV_MAT_ELEM_PTR(*segMat,y,x))=background;int rand=rng.uniform(0,defaultSubsamplingFactor);if(rand==0){rand=rng.uniform(0,defaultNbSamples);samples[y][x][rand]=CV_MAT_ELEM(*pFrameMat,float,y,x);}rand=rng.uniform(0,defaultSubsamplingFactor);if(rand==0){int xN,yN;rand=rng.uniform(0,9);yN=y+c_yoff[rand];if(yN<0) yN=0; if(yN>=pFrameMat->rows) yN=pFrameMat->rows-1;rand=rng.uniform(0,9);xN=x+c_xoff[rand];if(xN<0) xN=0; if(xN>=pFrameMat->cols) xN=pFrameMat->cols-1;rand=rng.uniform(0,defaultNbSamples);samples[yN][xN][rand]=CV_MAT_ELEM(*pFrameMat,float,y,x);}}else {//判断为前景像素*((float *)CV_MAT_ELEM_PTR(*segMat,y,x))=foreground;samples[y][x][defaultNbSamples]++;if(samples[y][x][defaultNbSamples]>50){int rand=rng.uniform(0,defaultNbSamples);if(rand==0){rand=rng.uniform(0,defaultNbSamples);samples[y][x][rand]=CV_MAT_ELEM(*pFrameMat,float,y,x);}}}}}}。