OpenCV霍夫变换(Hough Transform)直线检测详解

#include "opencv2/highgui.hpp"
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
 
#define PI 3.1415926
 
class LineFinder{
private:
 std::vector<cv::Vec2f> lines;
 double deltaRho; // 参数坐标系的步长(theta表示与直线垂直的角度)
 double deltaTheta;
 int minVote;  // 判断是直线的最小投票数 
public:
 LineFinder() {
 deltaRho = 1;
 deltaTheta = PI / 180;
 minVote = 80;
 }
 void setAccResolution(double dRho, double dTheta) {
 deltaRho = dRho;
 deltaTheta = dTheta;
 }
 void setMinVote(int minv) {
 minVote = minv;
 }
 // Hough变换检测直线;rho=1,theta=PI/180参数坐标系里的步长,threshold=最小投票数
 void findLines(cv::Mat& binary){
 lines.clear();
 cv::HoughLines(binary, lines, deltaRho, deltaTheta, minVote);
 }
 
 void drawDetectedLines(cv::Mat& result){
 std::vector<cv::Vec2f>::const_iterator it = lines.begin();
 while (it != lines.end())
 {
 // 以下两个参数用来检测直线属于垂直线还是水平线
 float rho = (*it)[0];
 float theta = (*it)[1];
 if (theta < PI / 4. || theta > 3.*PI / 4.)
 { // 若检测为垂直线,直线交于图片的上下两边,先找交点
 cv::Point pt1(rho / cos(theta), 0);
 cv::Point pt2((rho - result.rows*sin(theta)) / cos(theta), result.rows);
 cv::line(result, pt1, pt2, cv::Scalar(255), 1); //
 }
 else // 若检测为水平线,直线交于图片的左右两边,先找交点
 {
 cv::Point pt1(0, rho / sin(theta));
 cv::Point pt2(result.cols, (rho - result.cols*cos(theta)) / sin(theta));
 cv::line(result, pt1, pt2, cv::Scalar(255), 1);
 }
 ++it;
 }
 }
};
 
int main(int argc, char *argv[])
{
 cv::Mat image = cv::imread("D:/VS_exercise/images/road1.jpg");
 cv::Mat imageGray;
 cv::Mat contours;
 cv::cvtColor(image, imageGray, cv::COLOR_RGB2GRAY);
 cv::Canny(imageGray, contours, 190, 300);
 // 在原图的拷贝上画直线
 cv::Mat result(contours.rows, contours.cols, CV_8U, cv::Scalar(255));
 image.copyTo(result);
 // Hough变换检测
 LineFinder finder;
 finder.setMinVote(130);
 finder.findLines(contours);
 finder.drawDetectedLines(result);
 
 // 显示
 cv::namedWindow("Detected Lines with Hough");
 cv::imshow("Detected Lines with Hough", result);
 cv::waitKey(0);
 return 0;
}

#include "opencv2/highgui.hpp"
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
 
#define PI 3.1415926 
 
class LineFinder{
private:
 std::vector<cv::Vec4i> lines;
 double deltaRho; // 步长(theta表示与直线垂直的角度)
 double deltaTheta;
 int minVote;  // 判断是直线的最小投票数 
 double minLength; // 判断是直线的最小线段长度 
 double maxGap; // 允许组成连续线段的最大像素间隔
public:
 LineFinder() {
 deltaRho = 1;
 deltaTheta = PI / 180;
 minVote = 10;
 minLength = 0.0;
 maxGap = 0.0;
 }
 void setAccResolution(double dRho, double dTheta) {
 deltaRho = dRho;
 deltaTheta = dTheta;
 }
 void setMinVote(int minv) {
 minVote = minv;
 }
 void setLineLengthAndGap(double length, double gap) {
 minLength = length;
 maxGap = gap;
 }
 
 // Hough变换检测线段
 void findLines(cv::Mat& binary) {
 lines.clear();
 cv::HoughLinesP(binary, lines, deltaRho, deltaTheta, minVote, minLength, maxGap);
 }
 
 void drawDetectedLines(cv::Mat &image, cv::Scalar color = cv::Scalar(255)) {
 std::vector<cv::Vec4i>::const_iterator it2 = lines.begin();
 while (it2 != lines.end()) {
 cv::Point pt1((*it2)[0], (*it2)[1]);
 cv::Point pt2((*it2)[2], (*it2)[3]);
 cv::line(image, pt1, pt2, color, 1.5); //画线段
 ++it2;
 }
 }
};
 
int main(int argc, char *argv[])
{
 cv::Mat image = cv::imread("D:/VS_exercise/images/road1.jpg");
 cv::Mat imageGray;
 cv::Mat contours;
 cv::cvtColor(image, imageGray, cv::COLOR_RGB2GRAY);
 // 边缘检测
 cv::Canny(imageGray, contours, 190, 300);
 // Hough变换检测
 LineFinder finder;
 finder.setMinVote(80);
 finder.setLineLengthAndGap(100, 10); //概率Hough变换增加的两个参数
 finder.findLines(contours);
 finder.drawDetectedLines(image);
 
 // 显示
 cv::imshow("Detected Lines with Hough", image);
 cv::waitKey(0);
 return 0;
}