【OpenCV学习笔记】三十九、运动物体检测(一)

运动物体检测(一)

1.运动物体检测——背景减法

2.运动物体检测——帧差法

先上ppt：

代码：1.运动物体检测——背景减法

///运动物体检测——背景减法#include "opencv2/opencv.hpp"using namespace cv;#include <iostream>using namespace std;//运动物体检测函数声明Mat MoveDetect(Mat background,Mat frame);int main(){VideoCapture video("bike.avi");//定义VideoCapture类videoif (!video.isOpened())//对video进行异常检测{cout << "video open error!" << endl;return 0;}int frameCount = video.get(CV_CAP_PROP_FRAME_COUNT);//获取帧数double FPS = video.get(CV_CAP_PROP_FPS);//获取FPSMat frame;//存储帧Mat background;//存储背景图像Mat result;//存储结果图像for (int i = 0; i < frameCount; i++){video >> frame;//读帧进frameimshow("frame", frame);if (frame.empty())//对帧进行异常检测{cout << "frame is empty!" << endl;break;}int framePosition = video.get(CV_CAP_PROP_POS_FRAMES);//获取帧位置（第几帧）cout << "framePosition: " << framePosition << endl;if (framePosition == 1)//将第一帧作为背景图像background = frame.clone();result = MoveDetect(background, frame);//调用MoveDetect()进行运动物体检测，返回值存入resultimshow("result", result);if (waitKey(1000.0/FPS) == 27)//按原FPS显示{cout << "ESC退出!" << endl;break;}}return 0;}Mat MoveDetect(Mat background, Mat frame){Mat result = frame.clone();//1.将background和frame转为灰度图Mat gray1, gray2;cvtColor(background, gray1, CV_BGR2GRAY);cvtColor(frame, gray2, CV_BGR2GRAY);//2.将background和frame做差Mat diff;absdiff(gray1, gray2, diff);imshow("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("diff_thresh", diff_thresh);//4.腐蚀Mat kernel_erode = getStructuringElement(MORPH_RECT, Size(3, 3));Mat kernel_dilate = getStructuringElement(MORPH_RECT, Size(15, 15));erode(diff_thresh, diff_thresh, kernel_erode);imshow("erode", diff_thresh);//5.膨胀dilate(diff_thresh, diff_thresh, kernel_dilate);imshow("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]);rectangle(result, boundRect[i], Scalar(0, 255, 0), 2);//在result上绘制正外接矩形}return result;//返回result}

运行结果：

代码：2.运动物体检测——帧差法

///运动物体检测——帧差法#include "opencv2/opencv.hpp"using namespace cv;#include <iostream>using namespace std;//运动物体检测函数声明Mat MoveDetect(Mat temp, Mat frame);int main(){VideoCapture video("bike.avi");//定义VideoCapture类videoif (!video.isOpened())//对video进行异常检测{cout << "video open error!" << endl;return 0;}int frameCount = video.get(CV_CAP_PROP_FRAME_COUNT);//获取帧数double FPS = video.get(CV_CAP_PROP_FPS);//获取FPSMat frame;//存储帧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 >> frame;//读帧进frameimshow("frame", frame);if (frame.empty())//对帧进行异常检测{cout << "frame is empty!" << endl;break;}if (i == 0)//如果为第一帧（temp还为空）{result = MoveDetect(frame, frame);//调用MoveDetect()进行运动物体检测，返回值存入result}else//若不是第一帧（temp有值了）{result = MoveDetect(temp, frame);//调用MoveDetect()进行运动物体检测，返回值存入result}imshow("result", result);if (waitKey(1000.0 / FPS) == 27)//按原FPS显示{cout << "ESC退出!" << endl;break;}temp = frame.clone();}return 0;}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("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("diff_thresh", diff_thresh);//4.腐蚀Mat kernel_erode = getStructuringElement(MORPH_RECT, Size(3, 3));Mat kernel_dilate = getStructuringElement(MORPH_RECT, Size(18, 18));erode(diff_thresh, diff_thresh, kernel_erode);imshow("erode", diff_thresh);//5.膨胀dilate(diff_thresh, diff_thresh, kernel_dilate);imshow("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]);rectangle(result, boundRect[i], Scalar(0, 255, 0), 2);//在result上绘制正外接矩形}return result;//返回result}

运行结果：