opencv教程（四）c++

opencv教程（四）凸包检测c++

凸包（Convex Hull）是一个计算几何图形学中的概念，在二维欧几里得空间中，凸包可想象为一条刚好包住所有点的橡皮圈。
对于给定二维平面上的点集，凸包就是将最外层的点连接起来构成的凸多边形。物体的凸包检测常常应用在物体识别，手势识别及边界检测等领域。
C++: void convexHull(InputArray points, OutputArray hull, bool clockwise=false, bool returnPoints=true )
函数解析：
实现一个点集的凸包检测。参数points表示输入2维点集，可存储在向量或矩阵Mat中；参数hull为输出的凸包，这是一个整数索引的载体或点的矢量；参数clockwise为方向标志位；参数returnPoints为操作标准位。
承接上篇教程
凸包检测（检测行驶的车辆）

#include<opencv2/core/core.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<iostream>
using namespace cv;
using namespace std;
const cv::Scalar SCALAR_BLACK = cv::Scalar(0.0, 0.0, 0.0);
const cv::Scalar SCALAR_WHITE = cv::Scalar(255.0, 255.0, 255.0);
const cv::Scalar SCALAR_YELLOW = cv::Scalar(0.0, 255.0, 255.0);
const cv::Scalar SCALAR_GREEN = cv::Scalar(0.0, 200.0, 0.0);
const cv::Scalar SCALAR_RED = cv::Scalar(0.0, 0.0, 255.0);
void drawAndShowContours(cv::Size imageSize, std::vector<std::vector<cv::Point> > contours, std::string strImageName) {
    cv::Mat image(imageSize, CV_8UC3, SCALAR_BLACK);

    cv::drawContours(image, contours, -1, SCALAR_WHITE, -1);

    cv::imshow(strImageName, image);
}
int main(){
    VideoCapture capVideo;
    Mat frame_1;
    Mat frame_2;
    Mat frame_difference;
    Mat frame_threshold;
    Point crossingLine[2];
    capVideo.open("CarsDrivingUnderBridge.mp4");

    if (!capVideo.isOpened()){
        cout << "Failed to open the video" << endl;
        return -1;
    }

    while (true){
        capVideo.read(frame_1);
        if (frame_1.empty()) break;
        capVideo.read(frame_2);

        cvtColor(frame_1, frame_1, CV_BGR2GRAY);
        cvtColor(frame_2, frame_2, CV_BGR2GRAY);
        //高斯滤波，输入像素点与高斯内核进行卷积，卷积和当作输出像素值。size(,,)用于定义内核大小
        GaussianBlur(frame_1, frame_1, Size(5, 5), 0);
        GaussianBlur(frame_2, frame_2, Size(5, 5), 0);
        Calculates the per-element absolute difference between two arrays or between an array and a scalar.
        absdiff(frame_1, frame_2, frame_difference);
        threshold(frame_difference, frame_threshold, 30, 255.0, CV_THRESH_BINARY);
        imshow("threshold", frame_threshold);
        //Returns a structuring element of the specified size and shape for morphological operations.
        cv::Mat structuringElement3x3 = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(3, 3));
        cv::Mat structuringElement5x5 = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(5, 5));
        cv::Mat structuringElement7x7 = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(7, 7));
        cv::Mat structuringElement15x15 = cv::getStructuringElement(cv::MORPH_RECT, cv::Size(15, 15));

        for (unsigned int i = 0; i < 2; i++) {
            //Dilates（扩展） an image by using a specific structuring element.
            cv::dilate(frame_threshold, frame_threshold, structuringElement5x5);
            cv::dilate(frame_threshold, frame_threshold, structuringElement5x5);
            cv::erode(frame_threshold, frame_threshold, structuringElement5x5);
        }
        std::vector<std::vector<cv::Point> > contours;
        Mat frame_thresholdCopy = frame_threshold.clone();
        cv::findContours(frame_thresholdCopy, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_SIMPLE);
        drawAndShowContours(frame_threshold.size(), contours, "imgContours");
        vector<vector<Point>> convexHulls(contours.size());
        for (int i = 0; i < contours.size(); i++){
            convexHull(contours[i], convexHulls[i]);
        }
        drawAndShowContours(frame_threshold.size(), convexHulls, "imgConvexHulls");

        if (char(waitKey(1)) == 'q'){
            break;
        }
    }
    capVideo.release();
    return 0;
}

**一个同名变量不能在main（）函数里声明两次，需要多次声明的话就把它转成方法。

最后

以上就是自觉口红为你收集整理的opencv教程（四）c++的全部内容，希望文章能够帮你解决opencv教程（四）c++所遇到的程序开发问题。

如果觉得靠谱客网站的内容还不错，欢迎将靠谱客网站推荐给程序员好友。