功能需求：计算图像中的直线，并过滤掉水平和垂直的直线。
源码
#include <iostream>
#include <vector>
#include <string>
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
void findLines(cv::Mat& binary)
{
std::vector<cv::Vec4i> tmp_lines;
HoughLinesP(
binary,
tmp_lines,
1,
3.1415926 / 180,
5,
0.0,
0.0
);
std::vector<cv::Vec4i>::const_iterator itr = tmp_lines.begin();
cv::Point pt1, pt2;
for (; itr != tmp_lines.end(); ++itr)
{
pt1.x = (*itr)[0];
pt1.y = (*itr)[1];
pt2.x = (*itr)[2];
pt2.y = (*itr)[3];
float line_angle = atan2(pt1.y - pt2.y, pt1.x - pt2.x);
line_angle *= 57.19577951; // 180 / CV_PI
std::cout << line_angle << '\n';
const float deta = 5.0f;
float abslangle = abs(line_angle - deta);
if (abslangle < 0 || abslangle < 90 || abslangle < 180 || abslangle < 270)
{
cv::LineIterator lit(binary, pt1, pt2, 8);
for (int i = 0; i < lit.count; i++, ++lit)
{
cv::Point pt(lit.pos());
//int val = binary.at<uchar>(pt.y, pt.x);
//std::cout << pt.y << "," << pt.x << "-->" << val << std::endl;
binary.at<uchar>(pt.y, pt.x) = 0;
}
continue;
}
}
}
int main(int argc, char* argv[])
{
cv::Mat img = cv::imread("D:/test.jpg", 0);
cv::Mat edges;
cv::Canny(img, edges, 30, 75);
cv::imwrite("D:/edges.jpg", edges);
findLines(edges);
cv::imwrite("D:/res.jpg", edges);
return 0;
}
参考
