//#include "stdafx.h"
#include "windows.h"
#include "math.h"
#include "cv.h"
#include "cxcore.h"
#include "highgui.h"
#include "cvaux.h"
#include "ml.h"
/******************************************************主函数********************************************************/
int main(int argc, char argv[])
{
CvScalar color_tab[10];
color_tab[0] = CV_RGB(255, 0, 0);
color_tab[1] = CV_RGB(0, 255, 0);
color_tab[2] = CV_RGB(0, 0, 255);
color_tab[3] = CV_RGB(255, 0, 255);
color_tab[4] = CV_RGB(255, 255, 0);
CvCapture capture = cvCreateFileCapture("E:\shiyan\flow1.mov");
int fps = cvGetCaptureProperty(capture, CV_CAP_PROP_FPS); //获取视频文件的属性，帧率
IplImage* pFrame = NULL; //创建一个当前帧的指针
pFrame = cvQueryFrame(capture); //将下一帧加入内存（在cvCapture中分配了内存），返回对应当前帧的指针，
if (!pFrame)
{
printf("Bad frame /n");
exit(0);
}
CvGaussBGStatModelParams* params = new CvGaussBGStatModelParams; //直接调用高斯混合模型的函数
params->win_size = 1000; //学习效率a=1/win_size
params->n_gauss = 5; //5个混合高斯模型
params->bg_threshold = 0.1; //高斯背景阈值
params->std_threshold = 3.5; //lamuda=3.5
params->minArea = 30; //最小高斯核的面积
params->weight_init = 0.05; //初始权重为0.05
params->variance_init = 30; //初始标准差为30
CvBGStatModel* bgModel = cvCreateGaussianBGModel(pFrame, params); //创建高斯混合模型
while (1)
{
pFrame = cvQueryFrame(capture);
if (!pFrame)
break;
cvUpdateBGStatModel(pFrame, bgModel); //更新高斯混合模型
IplImage*img = bgModel->foreground; //指向前景
//cvConvexHull();
//printf("%d",img->);
int cols = 3, rows = 3, anchor_x = 1, anchor_y = 1;
int values[] = { 0, 1, 0,
1, 1, 0,
0, 0, 0 };
IplConvKernel*element = cvCreateStructuringElementEx(cols, rows, anchor_x, anchor_y, CV_SHAPE_CUSTOM, values); //自定义3x3的核
cvDilate(img, img, element, 4); //形态学膨胀，4次
IplImage*Img = cvCreateImage(cvGetSize(img), img->depth, img->nChannels);
cvCopy(img, Img);
CvMemStorage*storage, *stor; //创建存储空间指针
CvSeq*cont1, *cont2;
//创建序列指针
stor = cvCreateMemStorage(0);
//指向的存储位置
cont1 = cvCreateSeq(CV_SEQ_ELTYPE_POINT, sizeof(CvSeq), sizeof(CvPoint), stor);
cvFindContours(img, stor, &cont1, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_NONE, cvPoint(0, 0));
//cont=bgModel->foreground_regions;
int i = 0;
for (; cont1; cont1 = cont1->h_next)
{
if (cont1->total
continue;
cont2 = cvApproxPoly(cont1, sizeof(CvContour), stor, CV_POLY_APPROX_DP, cvContourPerimeter(cont1)*0.001, 0); //用四边形进行轮廓拟合
if (cvArcLength(cont2)>30 && fabs(cvContourArea(cont2))>200)
{
cvDrawContours(pFrame, cont2, CV_RGB(255, 0, 0), CV_RGB(255, 0, 0), 0, 1, 8, cvPoint(0, 0)); //画出轮廓
CvRect rect = cvContourBoundingRect(cont2); //确定边框区域
cvRectangle(pFrame, cvPoint(rect.x, rect.y), cvPoint(rect.x + rect.width, rect.y + rect.height), color_tab[i], 1, 8, 0);
i++;
cvRectangle(Img, cvPoint(rect.x, rect.y), cvPoint(rect.x + rect.width, rect.y + rect.height), CV_RGB(255, 255, 255), 1, 8, 0);
}
}
if (cvWaitKey(fps) == 'p')
{
cvWaitKey(0);
}
cvReleaseMemStorage(&stor);
cvShowImage("video", pFrame);
cvShowImage("FG", Img);
}
cvReleaseBGStatModel(&bgModel);
cvReleaseCapture(&capture);
return 0;
}
