【图像处理】c++使用opencv对图像进行轮廓识别

学习目标:学习使用C++对图像轮廓进行提取

文章目录

  • 轮廓提取的代码实现
  • 运行结果

轮廓提取的代码实现

#include 
#include 
#include 
#include 

using namespace cv;
using namespace std;

Mat src; Mat src_gray;
int thresh = 100;
int max_thresh = 255;
RNG rng(12345);

void thresh_callback(int, void*);

int main(int argc, char** argv)
{
    String imageName("./1.jpg"); 

    if (argc > 1)
    {
        imageName = argv[1];
    }

    src = imread(imageName, IMREAD_COLOR);
    if (src.empty())
    {
        cerr << "No image supplied ..." << endl;
        return -1;
    }
    cvtColor(src, src_gray, COLOR_BGR2GRAY);
    blur(src_gray, src_gray, Size(3, 3));
    const char* source_window = "Source";
    namedWindow(source_window, 0);
    imshow(source_window, src);
    createTrackbar(" Canny thresh:", "Source", &thresh, max_thresh, thresh_callback);
    thresh_callback(0, 0);
    waitKey(0);
    return(0);
}

void thresh_callback(int, void*)
{
    Mat canny_output;
    vector<vector<Point>> contours;
    vector<Vec4i> hierarchy;

    Canny(src_gray, canny_output, thresh, thresh*2, 3);
    findContours(canny_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));
    Mat drawing = Mat::zeros(canny_output.size(), CV_8UC1);  // 彩色轮廓使用3通道 CV_8UC3
    for (size_t i = 0; i < contours.size(); i++)
    {
        Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
        drawContours(drawing, contours, (int)i, color, 2, 8, hierarchy, 0, Point());
    }
    namedWindow("Contours", 0);
    imshow("Contours", drawing);
}

运行结果

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