https://t.cn/A6YaJxb2
#include
#include
#include
using namespace std;
using namespace cv;

int main()
{
Mat src = imread("1.jpg", 0);
//imshow("src", src);

Mat dst;
threshold(src, dst, 100, 255, CV_THRESH_BINARY_INV); //二值化
//imshow("dst", dst);

int nRows = dst.rows;
int nCols = dst.cols;

ofstream fout("data.txt");

//按列扫描，求像素和，由于是二值后的图片，没有线条时，该列的像素和为0；扫描到线条时像素大于0
for(int w = 0; w < nCols; w++)
{
int sum = 0;

for(int h = 0; h < nRows; h++)
{
uchar *pRow = dst.ptr(h, w); //该列中每个像素的地址
sum += (int)(*pRow);

if(sum > 0) //到达了线条的上侧，像素和大于0
{
cout << "找到了线条点,"; //从上往下找，由于线条很细，目前只判断上边界。
cout << "坐标如下： X = " << w << ", Y = " << h << endl;
fout << "坐标如下： X = " << w << ", Y = " << h << endl; //控制台会丢失数据，存到文本不会丢失
sum = 0;
break;
}
}
}

waitKey();
cout << endl;
system("pause");
return 0;
}

https://t.cn/A6YaJxby
opencv 九种直线检测方法汇总
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