OpenCV利用霍夫变换进行直线检测

#include "opencv2/opencv.hpp"
#define PI 3.1415926
 
int main(int argc, char *argv[])
{
 cv::Mat image = cv::imread ("road.jpg");
 cv::Mat result;
 cv::cvtColor (image,result,CV_BGRA2GRAY);
 cv::Mat contours;
 cv::Canny (result,contours,125,350); //边缘检测
 std::vector<cv::Vec2f> lines;
 /*霍夫变换,获得一组极坐标参数（rho，theta）,每一对对应一条直线，保存到lines
  第3,4个参数表示在（rho，theta)坐标系里横纵坐标的最小单位，即步长*/
 cv::HoughLines (contours,lines,1,PI/180,80);
 std::vector<cv::Vec2f>::const_iterator iter = lines.begin ();
 std::cout<<lines.size ()<<std::endl;
 while(iter != lines.end())
 {
  float rho = (*iter)[0];
  float theta = (*iter)[1];
  if(theta<PI/4.||theta>3.*PI/4)
 { //画交点在上下两边的直线
   cv::Point pt1(rho/cos(theta),0);
   cv::Point pt2((rho-result.rows*sin(theta))/cos(theta),result.rows);
   cv::line(image,pt1,pt2,cv::Scalar(255),1);
  }
  else 
  { //画交点在左右两边的直线
   cv::Point pt1(0,rho/sin(theta));
   cv::Point pt2(result.cols,(rho-result.cols*cos(theta)/sin(theta)));
   cv::line(image,pt1,pt2,cv::Scalar(255),1);
  }
  ++iter;
 }
 cv::namedWindow ("hough");
 cv::imshow("hough",image);
 cv::waitKey (0);
}

#include "opencv2/opencv.hpp"
#define PI 3.1415926
 
class LineFinder
{
private:
  std::vector<cv::Vec4i> lines; // 直线对应的点参数向量
  double deltaRho; //步长
  double deltaTheta;
  int minVote; // 判断是直线的最小投票数
  double minLength; // 判断是直线的最小长度
  double maxGap; // 同一条直线上点之间的距离容忍度
public:
  LineFinder() : deltaRho(1), deltaTheta(PI/180),
  minVote(10), minLength(0.), maxGap(0.) {} //初始化
 
  void setAccResolution(double dRho, double dTheta) // 设置步长
  {
   deltaRho= dRho;
   deltaTheta= dTheta;
  }
  
  void setMinVote(int minv) // 设置最小投票数
 {
   minVote= minv;
  }
  
  void setLineLengthAndGap(double length, double gap) // 设置最小线段长度和线段间距容忍度 
 {
   minLength= length;
   maxGap= gap;
  }
 
  
  std::vector<cv::Vec4i> findLines(cv::Mat& binary) //寻找线段
 {
   lines.clear();
   cv::HoughLinesP(binary,lines, deltaRho, deltaTheta, minVote,minLength, maxGap);
   return lines;
  }
 
  void drawDetectedLines(cv::Mat &image, cv::Scalar color=cv::Scalar(255,255,255)) // 画线段
 {
  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);
    ++it2;
   }
  }
};
 
int main(int argc, char *argv[])
{
 cv::Mat image = cv::imread ("road.jpg");
 cv::Mat result;
 cv::cvtColor (image,result,CV_BGRA2GRAY);
 cv::Mat contours;
 cv::Canny (result,contours,125,350); //边缘检测
 LineFinder finder;
 finder.setMinVote (80);
 finder.setLineLengthAndGap (100,20);
 finder.findLines (contours);
 finder.drawDetectedLines (image);
 std::vector<cv::Vec2f> lines;
 cv::HoughLines (contours,lines,1,PI/180,80);
 std::vector<cv::Vec2f>::const_iterator iter = lines.begin ();
 std::cout<<lines.size ()<<std::endl;
 while(iter != lines.end())
 {
  float rho = (*iter)[0];
  float theta = (*iter)[1];
  if(theta<PI/4.||theta>3.*PI/4)
 { //画交点在上下两边的直线
   cv::Point pt1(rho/cos(theta),0);
   cv::Point pt2((rho-result.rows*sin(theta))/cos(theta),result.rows);
   cv::line(image,pt1,pt2,cv::Scalar(255),1);
  }
  else 
  { //画交点在左右两边的直线
   cv::Point pt1(0,rho/sin(theta));
   cv::Point pt2(result.cols,(rho-result.cols*cos(theta)/sin(theta)));
   cv::line(image,pt1,pt2,cv::Scalar(255),1);
  }
  ++iter;
 }
 cv::namedWindow ("hough");
 cv::imshow("hough",image);
 cv::waitKey (0);
}