samples/cpp/tutorial_code/ImgTrans/houghlines.cpp

一個使用霍夫線檢測器的例子

 
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
 
using namespace cv;
using namespace std;
 
int main(int argc, char** argv)
{
    // 宣告輸出變數
    Mat dst, cdst, cdstP;
 
    const char* default_file = "sudoku.png";
    const char* filename = argc >=2 ? argv[1] : default_file;
 
    // 載入影像
    Mat src = imread( samples::findFile( filename ), IMREAD_GRAYSCALE );
 
    // 檢查影像是否載入成功
    if(src.empty()){
printf(" Error opening image\n");
printf(" Program Arguments: [image_name -- default %s] \n", default_file);
        return -1;
    }
 
    // 邊緣檢測
Canny(src, dst, 50, 200, 3);
 
    // 複製邊緣到將以 BGR 顯示結果的影像
cvtColor(dst, cdst, COLOR_GRAY2BGR);
cdstP = cdst.clone();
 
    // 標準霍夫線變換
vector<Vec2f> lines; // 將儲存檢測結果
HoughLines(dst, lines, 1, CV_PI/180, 150, 0, 0 ); // 執行實際檢測
    // 繪製線條
    for( size_t i = 0; i < lines.size(); i++ )
    {
        float rho = lines[i][0], theta = lines[i][1];
        Point pt1, pt2;
        double a = cos(theta), b = sin(theta);
        double x0 = a*rho, y0 = b*rho;
pt1.x = cvRound(x0 + 1000*(-b));
pt1.y = cvRound(y0 + 1000*(a));
pt2.x = cvRound(x0 - 1000*(-b));
pt2.y = cvRound(y0 - 1000*(a));
line( cdst, pt1, pt2, Scalar(0,0,255), 3, LINE_AA);
    }
 
    // 機率霍夫線變換
vector<Vec4i> linesP; // 將儲存檢測結果
HoughLinesP(dst, linesP, 1, CV_PI/180, 50, 50, 10 ); // 執行實際檢測
    // 繪製線條
    for( size_t i = 0; i < linesP.size(); i++ )
    {
        Vec4i l = linesP[i];
line( cdstP, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0,0,255), 3, LINE_AA);
    }
 
    // 顯示結果
imshow("Source", src);
imshow("Detected Lines (in red) - Standard Hough Line Transform", cdst);
imshow("Detected Lines (in red) - Probabilistic Line Transform", cdstP);
 
    // 等待並退出
cv::Mat::empty
    return 0;
}