基于opencv进行摄像头精准识别检测追踪小球系统c++代码

以下是基于OpenCV进行摄像头精准识别检测追踪小球的C++代码：

#include <iostream>
#include <opencv2/opencv.hpp>

using namespace std;
using namespace cv;

int main(int argc, char** argv)
{
    VideoCapture cap(0);
    if (!cap.isOpened())
    {
        cout << "Failed to open camera!" << endl;
        return -1;
    }

    namedWindow("Ball Tracking", WINDOW_AUTOSIZE);

    int lowH = 0, lowS = 155, lowV = 0;
    int highH = 10, highS = 255, highV = 255;
    Mat frame, frame_HSV, frame_threshold;

    while (true)
    {
        bool ret = cap.read(frame);
        if (!ret)
        {
            cout << "Failed to read frame from camera!" << endl;
            break;
        }

        cvtColor(frame, frame_HSV, COLOR_BGR2HSV);
        inRange(frame_HSV, Scalar(lowH, lowS, lowV), Scalar(highH, highS, highV), frame_threshold);

        erode(frame_threshold, frame_threshold, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));
        dilate(frame_threshold, frame_threshold, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));

        dilate(frame_threshold, frame_threshold, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));
        erode(frame_threshold, frame_threshold, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));

        vector<vector<Point>> contours;
        vector<Vec4i> hierarchy;
        findContours(frame_threshold, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE);

        vector<vector<Point>> contours_poly(contours.size());
        vector<Rect> boundRect(contours.size());
        Point2f center;
        float radius = 0;

        for (size_t i = 0; i < contours.size(); i++)
        {
            approxPolyDP(contours[i], contours_poly[i], 3, true);
            boundRect[i] = boundingRect(contours_poly[i]);
            minEnclosingCircle(contours_poly[i], center, radius);
        }

        for (size_t i = 0; i < contours.size(); i++)
        {
            if (radius > 10)
            {
                rectangle(frame, boundRect[i].tl(), boundRect[i].br(), Scalar(0, 255, 0), 2, 8, 0);
                circle(frame, center, radius, Scalar(0, 0, 255), 2, 8, 0);
            }
        }

        imshow("Ball Tracking", frame);

        if (waitKey(30) == 27)
        {
            cout << "ESC key is pressed by user!" << endl;
            break;
        }
    }

    return 0;
}

该代码使用了OpenCV的VideoCapture类来读取摄像头的图像，并使用inRange函数进行图像阈值分割，得到二值化图像。然后通过形态学操作（腐蚀和膨胀）对图像进行处理，使得图像中的小球能够更加准确地被检测到。接着使用findContours函数和minEnclosingCircle函数来找到小球的轮廓和最小外接圆。最后将检测到的小球用矩形和圆形标记出来，并在窗口中显示出来。