实现目标
在透视变换的基础上，利用帧差法检测运动物体，并用矩形框出。
程序
#include<opencv2/opencv.hpp> #include<opencv2/highgui/highgui.hpp> #include<opencv2/core/core.hpp> #include<opencv2/imgproc/imgproc.hpp> #include <iostream> using namespace cv; using namespace std; Mat MoveDetect(Mat temp, Mat frame); void onMouse(int event, int x, int y, int flags, void *utsc); Point2f srcTri[4], dstTri[4]; int clickTimes = 0; Mat imageWarp; Mat frame; int main() { VideoCapture video("H:\\test.mp4"); if (!video.isOpened()) return -1; video.set(CV_CAP_PROP_FRAME_WIDTH, 1280); video.set(CV_CAP_PROP_FRAME_HEIGHT, 720); while (1) { int frameCount = video.get(CV_CAP_PROP_FRAME_COUNT);//获取帧数 double FPS = video.get(CV_CAP_PROP_FPS);//获取FPS Mat temp;//存储前一帧图像 Mat result;//存储结果图像 for (int i = 0; i < frameCount; i++) { video.read(frame); if (frame.empty())//异常检测 { cout << "frame is empty!" << endl; break; } if (i == 0)//如果为第一帧（temp为空） { result = MoveDetect(frame, frame); } else//若不是第一帧（temp有值） { result = MoveDetect(temp, frame); } temp = frame.clone(); imshow("result", result); setMouseCallback("Source Image", onMouse); imshow("Source Image", frame); } } return 0; } void onMouse(int event, int x, int y, int flags, void *utsc) { if (event == CV_EVENT_LBUTTONUP)//响应鼠标左键抬起事件 { circle(frame, Point(x, y), 2.5, Scalar(0, 0, 255), 2.5);//标记选中点 imshow("Source Image", frame); srcTri[clickTimes].x = x; srcTri[clickTimes].y = y; cout << "x: " << x << " y: " << y << endl; clickTimes++; } if (clickTimes == 4) { //注意点的顺序：左上，右上，左下，右下 dstTri[0].x = 0; dstTri[0].y = 0; dstTri[1].x = frame.rows - 1; dstTri[1].y = 0; dstTri[2].x = 0; dstTri[2].y = frame.cols - 161; dstTri[3].x = frame.rows - 1; dstTri[3].y = frame.cols - 161; Mat transform = Mat::zeros(3, 3, CV_32FC1);//透视变换矩阵 transform = getPerspectiveTransform(srcTri, dstTri);//获取透视变换矩阵 warpPerspective(frame, imageWarp, transform, Size(frame.rows, frame.cols - 160));//透视变换 imshow("After WarpPerspecttive", imageWarp); } } Mat MoveDetect(Mat temp, Mat frame) { Mat result = frame.clone(); //1.将background和frame转为灰度图 Mat gray1, gray2; cvtColor(temp, gray1, CV_BGR2GRAY); cvtColor(frame, gray2, CV_BGR2GRAY); //2.将background和frame做差 Mat diff; absdiff(gray1, gray2, diff); // imshow("2_diff", diff); //3.对差值图diff_thresh进行阈值化处理 Mat diff_thresh; threshold(diff, diff_thresh, 50, 255, CV_THRESH_BINARY); // imshow("3_diff_thresh", diff_thresh); //4.腐蚀 Mat kernel_erode = getStructuringElement(MORPH_RECT, Size(3, 3)); Mat kernel_dilate = getStructuringElement(MORPH_RECT, Size(5, 5)); erode(diff_thresh, diff_thresh, kernel_erode); // imshow("4_erode", diff_thresh); //5.膨胀 dilate(diff_thresh, diff_thresh, kernel_dilate); // imshow("5_dilate", diff_thresh); //6.查找轮廓并绘制轮廓 vector<vector<Point> > contours; findContours(diff_thresh, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE); // drawContours(result, contours, -1, Scalar(0, 0, 255), 2);//在result上绘制轮廓 //7.查找正外接矩形 vector<Rect> boundRect(contours.size()); for (int i = 0; i < contours.size(); i++) { boundRect[i] = boundingRect(contours[i]); if (contours[i].size() > 500)//过滤掉较小的矩形 rectangle(result, boundRect[i], Scalar(0, 255, 0), 2);//在result上绘制正外接矩形 } return result; }
