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使用opencv怎么解析三帧差法?很多新手对此不是很清楚,为了帮助大家解决这个难题,下面小编将为大家详细讲解,有这方面需求的人可以来学习下,希望你能有所收获。
#include<iostream> #include<opencv2\core\core.hpp> #include<opencv2\highgui\highgui.hpp> #include<opencv2\imgproc\imgproc.hpp> using namespace cv; using namespace std; const unsigned char FORE_GROUD = 255;int thresh = 10; int main(int argc,char*argv[]) { VideoCapture video(argv[1]); //判断如果video是否可以打开 if(!video.isOpened()) return -1; //用于保存当前帧的图片 Mat currentBGRFrame; //用来保存上一帧和当前帧的灰度图片 Mat previousSecondGrayFrame; Mat previousFirstGrayFrame; Mat currentGaryFrame; //保存两次的帧差 Mat previousFrameDifference; //previousFrameFirst - previousFrameSecond的差分 Mat currentFrameDifference; //currentFrame - previousFrameFirst; //用来保存帧差的绝对值 Mat absFrameDifferece; //用来显示前景 Mat previousSegmentation; Mat currentSegmentation; Mat segmentation; //显示前景 namedWindow("segmentation",1); createTrackbar("阈值:","segmentation",&thresh,FORE_GROUD,NULL); //帧数 int numberFrame = 0; //形态学处理用到的算子 Mat morphologyKernel = getStructuringElement(MORPH_RECT,Size(3,3),Point(-1,-1)); for(;;) { //读取当前帧 video >> currentBGRFrame; //判断当前帧是否存在 if(!currentBGRFrame.data) break; numberFrame++; //颜色空间的转换 cvtColor(currentBGRFrame,currentGaryFrame,COLOR_BGR2GRAY); if( numberFrame == 1) { //保存当前帧的灰度图 previousSecondGrayFrame = currentGaryFrame.clone(); //显示视频 imshow("video",currentBGRFrame); continue; } else if( numberFrame == 2) { //保存当前帧的灰度图 previousFirstGrayFrame = currentGaryFrame.clone(); //previousFirst - previousSecond subtract(previousFirstGrayFrame,previousSecondGrayFrame,previousFrameDifference,Mat(),CV_16SC1); //取绝对值 absFrameDifferece = abs(previousFrameDifference); //位深的改变 absFrameDifferece.convertTo(absFrameDifferece,CV_8UC1,1,0); //阈值处理 threshold(absFrameDifferece,previousSegmentation,double(thresh),double(FORE_GROUD),THRESH_BINARY); //显示视频 imshow("video",currentBGRFrame); continue; } else { //src1-src2 subtract(currentGaryFrame,previousFirstGrayFrame,currentFrameDifference,Mat(),CV_16SC1); //取绝对值 absFrameDifferece = abs(currentFrameDifference); //位深的改变 absFrameDifferece.convertTo(absFrameDifferece,CV_8UC1,1,0); //阈值处理 threshold(absFrameDifferece,currentSegmentation,double(thresh),double(FORE_GROUD),THRESH_BINARY); //与运算 bitwise_and(previousSegmentation,currentSegmentation,segmentation); //中值滤波 medianBlur(segmentation,segmentation,3); //形态学处理(开闭运算) //morphologyEx(segmentation,segmentation,MORPH_OPEN,morphologyKernel,Point(-1,-1),1,BORDER_REPLICATE); morphologyEx(segmentation,segmentation,MORPH_CLOSE,morphologyKernel,Point(-1,-1),2,BORDER_REPLICATE); //找边界 vector< vector<oint> > contours; vector<Vec4i> hierarchy; //复制segmentation Mat tempSegmentation = segmentation.clone(); findContours( segmentation, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );//CV_RETR_TREE vector< vector<oint> > contours_poly( contours.size() ); /*存储运动物体*/ vector<Rect> boundRect; boundRect.clear(); //画出运动物体 for(int index = 0;index < contours.size() ;index++) { approxPolyDP( Mat(contours[index]), contours_poly[index], 3, true ); Rect rect = boundingRect( Mat(contours_poly[index]) ); rectangle(currentBGRFrame,rect,Scalar(0,255,255),2); } //显示视频 imshow("video",currentBGRFrame); //前景检测 imshow("segmentation",segmentation); //保存当前帧的灰度图 previousFirstGrayFrame = currentGaryFrame.clone(); //保存当前的前景检测 previousSegmentation = currentSegmentation.clone(); } if(waitKey(33) == 'q') break; } return 0; }
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