運動物體檢測——幀差法&///運動物體檢測——背景減法

1、注意，使用的是opencv3,所以在cmakelists.txt加上（系統默認安裝的是opencv2）

set(OpenCV_DIR /usr/local/opencv3/share/OpenCV)

2、在cmakelists.txt加上

add_executable(node1 src/node1.cpp)
target_link_libraries(node1
  ${catkin_LIBRARIES}
)


add_executable(node2 src/node2.cpp)
target_link_libraries(node2
  ${catkin_LIBRARIES}
)

運動物體檢測——幀差法

///運動物體檢測——幀差法
#include "opencv2/opencv.hpp"
using namespace cv;
#include <iostream>
using namespace std;
//運動物體檢測函數聲明
Mat MoveDetect(Mat temp, Mat frame);

int main()
{

    VideoCapture video("/home/ly/1.mp4");//定義VideoCapture類video
    if (!video.isOpened())  //對video進行異常檢測
    {
        cout << "video open error!" << endl;
        return 0;
    }
    int frameCount = video.get(CV_CAP_PROP_FRAME_COUNT);//獲取幀數
    double FPS = video.get(CV_CAP_PROP_FPS);//獲取FPS
    Mat frame;//存儲幀
    Mat temp;//存儲前一幀圖像
    Mat result;//存儲結果圖像
    for (int i = 0; i < frameCount; i++)
    {

        video >> frame;//讀幀進frame
        imshow("frame", frame);
        if (frame.empty())//對幀進行異常檢測
        {
            cout << "frame is empty!" << endl;
            break;
        }
        if (i == 0)//如果爲第一幀（temp還爲空）
        {
            result = MoveDetect(frame, frame);//調用MoveDetect()進行運動物體檢測，返回值存入result
        }
        else//若不是第一幀（temp有值了）
        {
            result = MoveDetect(temp, frame);//調用MoveDetect()進行運動物體檢測，返回值存入result

        }
        imshow("result", result);
        if (waitKey(1000.0 / FPS) == 27)//按原FPS顯示
        {
            cout << "ESC退出!" << endl;
            break;
        }
        temp = frame.clone();
    }
    return 0;


}
Mat MoveDetect(Mat temp, Mat frame)
{
    Mat result = frame.clone();
    //1.將background和frame轉爲灰度圖
    Mat gray1, gray2;
    cvtColor(temp, gray1, CV_BGR2GRAY);
    cvtColor(frame, gray2, CV_BGR2GRAY);
    //2.將background和frame做差
    Mat diff;
    absdiff(gray1, gray2, diff);
    imshow("diff", diff);
    //3.對差值圖diff_thresh進行閾值化處理
    Mat diff_thresh;
    threshold(diff, diff_thresh, 50, 255, CV_THRESH_BINARY);
    imshow("diff_thresh", diff_thresh);
    //4.腐蝕
    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.膨脹
    dilate(diff_thresh, diff_thresh, kernel_dilate);
    imshow("dilate", diff_thresh);
    //6.查找輪廓並繪製輪廓
    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上繪製輪廓
    //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上繪製正外接矩形
    }
    return result;//返回result
}

運動物體檢測——背景減法

///運動物體檢測——背景減法
/// https://blog.csdn.net/abc8730866/article/details/70170267
#include "opencv2/opencv.hpp"
using namespace cv;
#include <iostream>
using namespace std;
//運動物體檢測函數聲明
Mat MoveDetect(Mat background,Mat frame);

int main()
{

    VideoCapture video("/home/ly/1.mp4");//定義VideoCapture類video
    if (!video.isOpened())  //對video進行異常檢測
    {
        cout << "video open error!" << endl;
        return 0;
    }
    int frameCount = video.get(CV_CAP_PROP_FRAME_COUNT);//獲取幀數
    double FPS = video.get(CV_CAP_PROP_FPS);//獲取FPS
    Mat frame;//存儲幀
    Mat background;//存儲背景圖像
    Mat result;//存儲結果圖像
    for (int i = 0; i < frameCount; i++)
    {
        video >> frame;//讀幀進frame
        imshow("frame", frame);
        if (frame.empty())//對幀進行異常檢測
        {
            cout << "frame is empty!" << endl;
            break;
        }
        int framePosition = video.get(CV_CAP_PROP_POS_FRAMES);//獲取幀位置（第幾幀）
        cout << "framePosition: " << framePosition << endl;
        if (framePosition == 1)//將第一幀作爲背景圖像
            background = frame.clone();
        result = MoveDetect(background, frame);//調用MoveDetect()進行運動物體檢測，返回值存入result
        imshow("result", result);
        if (waitKey(1000.0/FPS) == 27)//按原FPS顯示
        {
            cout << "ESC退出!" << endl;
            break;
        }
    }
    return 0;
}
Mat MoveDetect(Mat background, Mat frame)
{
    Mat result = frame.clone();
    //1.將background和frame轉爲灰度圖
    Mat gray1, gray2;
    cvtColor(background, gray1, CV_BGR2GRAY);
    cvtColor(frame, gray2, CV_BGR2GRAY);
    //2.將background和frame做差
    Mat diff;
    absdiff(gray1, gray2, diff);
    imshow("diff", diff);
    //3.對差值圖diff_thresh進行閾值化處理
    Mat diff_thresh;
    threshold(diff, diff_thresh, 50, 255, CV_THRESH_BINARY);
    imshow("diff_thresh", diff_thresh);
    //4.腐蝕
    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.膨脹
    dilate(diff_thresh, diff_thresh, kernel_dilate);
    imshow("dilate", diff_thresh);
    //6.查找輪廓並繪製輪廓
    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上繪製輪廓
    //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上繪製正外接矩形
    }
    return result;//返回result
}