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车道线检测算法经典编程

发布时间：2023/11/28 生活经验 33 豆豆

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车道线检测算法经典编程

车道线曲线拟合算法编程

计算经过（50，50），（90，120），（70，200）三点的Catmull_Rom样条曲线。

IplImage* img = cvCreateImage(cvSize(300,300), 8, 1);
for (int i = 0; i < img->height; ++i)
{

   for (int j = 0; j < img->width; ++j)

```
   {  
```

       ((char *)(img->imageData + img->widthStep * (i)))[j] = 0;

```
   }  
```
}
CvPoint point0,point1,point2,point3,point4;//3个控制点来做
point1.x = 50;
point1.y = 50;
point2.x = 90;
point2.y = 120;
point3.x = 70;
point3.y = 200;
point0.x = point1.x+(point1.x-point2.x);
point0.y = point1.y+(point1.y-point2.y);
point4.x = point3.x+(point3.x-point2.x);
point4.y = point3.y+(point3.y-point2.y);
((char *)(img->imageData + img->widthStep * (point1.y)))[point1.x] = 255;
((char *)(img->imageData + img->widthStep * (point2.y)))[point2.x] = 255;
((char *)(img->imageData + img->widthStep * (point3.y)))[point3.x] = 255;
for (int i = 1; i < 500 ; i++) {

         float t = (float) i * (1.0f / (float) 500);

```
         float tt = t * t;  
```
```
         float ttt = tt * t;  
```
```
      CvPoint pi;  
```

      pi.x = 0.5 * (2*point1.x+(point2.x-point0.x)*t + (2*point0.x-5*point1.x+4*point2.x-point3.x)*tt + (3*point1.x-point0.x-3*point2.x+point3.x)*ttt);

         pi.y = 0.5 * (2*point1.y+(point2.y-point0.y)*t + (2*point0.y-5*point1.y+4*point2.y-point3.y)*tt + (3*point1.y-point0.y-3*point2.y+point3.y)*ttt);

      ((char *)(img->imageData + img->widthStep * (pi.y)))[pi.x] = 255;

}
for (int i = 1; i < 500 ; i++) {

         float t = (float) i * (1.0f / (float) 500);

```
         float tt = t * t;  
```
```
         float ttt = tt * t;  
```
```
      CvPoint pi;  
```

      pi.x = 0.5 * (2*point2.x+(point3.x-point1.x)*t + (2*point1.x-5*point2.x+4*point3.x-point4.x)*tt + (3*point2.x-point1.x-3*point3.x+point4.x)*ttt);

         pi.y = 0.5 * (2*point2.y+(point3.y-point1.y)*t + (2*point1.y-5*point2.y+4*point3.y-point4.y)*tt + (3*point2.y-point1.y-3*point3.y+point4.y)*ttt);

      ((char *)(img->imageData + img->widthStep * (pi.y)))[pi.x] = 255;

}
cvShowImage(“scr”, img);
cvWaitKey(0);
return 0;
检测出Hough空间的曲线，规定如下搜索方法：

霍夫空间中相交的曲线越多，交点表示的线在笛卡尔坐标系对应的点越多。我们在霍夫空间中定义交点的最小阈值来检测线。霍夫变换跟踪了帧中的每个点的霍夫空间交点。如果交点数量超过了阈值就确定一条对应参数 θ 和 d的线。

1>起始搜索点为A点

2>向右搜索，直到退出，退出点为B

3>从B点向左搜索，直到退出

4>起始搜索点回到A点

5>向左搜索，直到退出，退出点为C

6>从C点向右搜索，直到退出

结束

部分代码如下：

向左搜索：

CvPoint searchRight(int HoughArea, IplImage hough, CvPoint point, Lines line)
{//找当前点的上、右上、右、右下、下

   //循环搜索，直到两个方向搜索均无结果，则退出开始下一步判断

   CvPoint start;//搜索的初始点

   start = point;//先将point作为当前的初始点

```
   int Max = 0;//找局部最大值  
```

   CvPoint last = start;//记录上一次最大值，本次搜索排除当前点和上一次点

   int mistakes = 0;//引入一个容错因子

   //****************************搜索上，右上，右，右下，下*****************************8

```
  while(1)  
```
```
  {  
```
```
      CvPoint temp;  
```

      if(start.x >= hough->width-1 || start.y <= 0||start.y >= hough->height-1)//超出搜索范围，退出搜索

```
          break;  
```
```
      //cout << "curve1" << endl;  
```
```
      for(int xx = 0;xx < 2; xx++)  
```
```
      {  
```

          for(int yy = -1;yy < 2;yy++)

```
          {  
```

              if((xx == 0 && yy == 0)||(start.y + yy == last.y && start.x + xx == last.x))//不包括当前点

```
                  continue;  
```

              //cout << HoughArea[start.y + yy][start.x + xx] << endl;

              if(HoughArea[start.y + yy][start.x + xx] > Max)

```
              {  
```

                  Max = HoughArea[start.y + yy][start.x + xx];

                  temp.x = start.x + xx;

                  temp.y = start.y + yy;

```
              }   
```
```
          }  
```
```
      }  
```
```
      if(Max > Threshold)  
```
```
      {  
```
```
          //cout << Max << "  ";  
```

          mistakes = 0;//容错清零

          cout << "find1:"<< Max << endl;

```
          Max = 0;  
```

          (*line).houghpoint.push_back(temp);

          last = start;//保存上一次最大值

          start = temp;//找到的点作为当前点继续搜索

```
          CvScalar s;      
```
```
          s.val[0]=0;  
```
```
          s.val[1]=255;  
```
```
          s.val[2]=0;  
```

          //cvSet2D(hough,temp.y,temp.x,s);//set the (i,j) pixel value

```
      }  
```

      else if(mistakes <= 5)//容错，三次

```
      {  
```
```
          mistakes++;  
```
```
          Max = 0;  
```
```
          start.x = start.x + 1;  
```
```
      }  
```
```
      else//退出条件  
```

          break;//没有找到符合条件的点，退出搜索

```
  }  
```

  //*******************************************************************************

```
  CvPoint final;  
```
```
  final.x = start.x - mistakes;  
```
```
  final.y = start.y;  
```
```
  return final;  
```
}
导入包含的库文件

#include

#include
<opencv2/opencv.hpp>

#include

#include
<opencv2/highgui/highgui.hpp>

#include

using namespace
std;

using namespace cv;

读取图片

//reading
image*****

Mat image;

image = imread("/home/project1/test1.jpg");

if(image.empty()){
```
 cout <<"reading error"<<endl;return -1;
```

}

灰度变换

//gray image****

Mat image_gray;

cvtColor(image,image_gray,
CV_BGR2GRAY);

canny边缘检测

//canny***

Mat image_canny;

Canny(image_gau,
image_canny,100, 200, 3);

总结

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