车道线检测算法经典编程

1. 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。

1. IplImage* img = cvCreateImage(cvSize(300,300), 8, 1);

2. for (int i = 0; i < img->height; ++i)

3. {

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

5. {

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

7. }

8. }

9. CvPoint point0,point1,point2,point3,point4;//3个控制点来做

10. point1.x = 50;

11. point1.y = 50;

12. point2.x = 90;

13. point2.y = 120;

14. point3.x = 70;

15. point3.y = 200;

16. point0.x = point1.x+(point1.x-point2.x);

17. point0.y = point1.y+(point1.y-point2.y);

18. point4.x = point3.x+(point3.x-point2.x);

19. point4.y = point3.y+(point3.y-point2.y);

20.

21. ((char *)(img->imageData + img->widthStep * (point1.y)))[point1.x] = 255;

22. ((char *)(img->imageData + img->widthStep * (point2.y)))[point2.x] = 255;

23. ((char *)(img->imageData + img->widthStep * (point3.y)))[point3.x] = 255;

24.

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

26.

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

28. float tt = t * t;

29. float ttt = tt * t;

30. CvPoint pi;

31. 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);

32. 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);

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

34. }

35.

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

37.

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

39. float tt = t * t;

40. float ttt = tt * t;

41. CvPoint pi;

42. 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);

43. 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);

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

45. }

46. cvShowImage("scr", img);

47. cvWaitKey(0);

48. return 0;

2. 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：

1. CvPoint searchRight(int **HoughArea, IplImage* hough, CvPoint point, Lines* line)

2. {//找当前点的上、右上、右、右下、下

3. //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

4. CvPoint start;//搜索的初始点

5. start = point;//先将point作为当前的初始点

6. int Max = 0;//找局部最大值

7. 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

8. int mistakes = 0;//引入一个容错因子

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

10. while(1)

11. {

12. CvPoint temp;

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

14. break;

15. //cout << "curve1" << endl;

16. for(int xx = 0;xx < 2; xx++)

17. {

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

19. {

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

21. continue;

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

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

24. {

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

26. temp.x = start.x + xx;

27. temp.y = start.y + yy;

28. }

29. }

30. }

31. if(Max > Threshold)

32. {

33. //cout << Max << " ";

34. mistakes = 0;//容错清零

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

36. Max = 0;

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

38. last = start;//保存上一次最大值

39. start = temp;//找到的点作为当前点继续搜索

40. CvScalar s;

41. s.val[0]=0;

42. s.val[1]=255;

43. s.val[2]=0;

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

45. }

46. else if(mistakes <= 5)//容错，三次

47. {

48. mistakes++;

49. Max = 0;

50. start.x = start.x + 1;

51. }

52. else//退出条件

53. break;//没有找到符合条件的点，退出搜索

54. }

55. //*******************************************************************************

56. CvPoint final;

57. final.x = start.x - mistakes;

58. final.y = start.y;

59. return final;

60. }

3. 导入包含的库文件

#include <iostream>

#include <opencv2/opencv.hpp>

#include<vector>

#include <opencv2/highgui/highgui.hpp>

#include<string>

using namespace std;

using namespace cv;

4. 读取图片

//*************reading image******************

Mat image;

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

if(image.empty()){

cout <<"reading error"<<endl;

return -1;

}

5. 灰度变换

//***************gray image*******************

Mat image_gray;

cvtColor(image,image_gray, CV_BGR2GRAY);

6. canny边缘检测

//******************canny*********************

Mat image_canny;

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