车道线检测代码（OpenCv）以及理论算法说明

//---------------------车道线检测-------------------------// /*可以处理摄像头，也可以处理视频文件*/ #include <opencv2/opencv.hpp> #include <iostream> #include <stdio.h> #include <string> #include <cv.h> #include <math.h> using namespace cv; using namespace std; CvCapture* g_capture = NULL; IplImage* PreProcessImg = NULL; CvPoint point1, point2, point3, pointend, pointtemp; CvPoint pointmeet;//相交点 vector<CvPoint> points; vector<CvPoint> pointsleft; vector<CvPoint> pointsright; //结构体1，左侧的线，右侧的线 struct line { CvPoint pointbottom; CvPoint pointtop; }lineleft, lineright; //结构体2 struct greycount { uchar grey; int count; }; //大津阈值,车道从背景中分离出来 void ImproveOTSU(IplImage* image, IplImage* image2) { //int lc = cvRound((image->height / 2) + 1); //cvSetImageROI(image, cvRect(0, lc, image->width, image->height)); //如果只对下半幅图像做大津阈值，效果不好 //cvThreshold(image, image, 80, 255, CV_THRESH_BINARY);//速度慢，与OSTU差100ms //cvThreshold(image, image2, 180, 235, CV_THRESH_BINARY_INV | CV_THRESH_OTSU);//BINARY能检测出视频3-2 cvThreshold(image, image2, 0, 255, CV_THRESH_OTSU);//改变阈值没效果 //cvResetImageROI(image); //cvCopy(image, image2); } //改进的hough变换检测车道 int Hough(IplImage* image, float* tabSin, float *tabCos, int *accum, int numrho, int &predistance1, int &preangle1, int &predistance2, int &preangle2) { int r, angle1 = 1, angle2 = 1, distance1 = 0, distance2 = 0, n = 0; long j; int angelstart1 = 40; int angleend1 = 70; int anglestart2 = 110; int angleend2 = 160; if (preangle1 != 0) { angelstart1 = preangle1 - 5; angleend1 = preangle1 + 5; } if (preangle2 != 0) { anglestart2 = preangle2 - 5; angleend2 = preangle2 + 5; } int step = image->widthStep / sizeof(uchar); uchar *data0 = (uchar *)image->imageData; for (int i = image->height / 2; i < image->height; i++) { for (j = 0; j < image->width; j++) { if (data0[i*step + j] == 255)//?? { for (n = angelstart1; n < angleend1; n++)//40--70 { r = cvRound(j * tabCos[n] + i * tabSin[n]); r += (numrho - 1) / 2; accum[(n + 1) * (numrho + 2) + r + 1]++; } for (n = anglestart2; n < angleend2; n++)//110--160 { r = cvRound(j * tabCos[n] + i * tabSin[n]); r += (numrho - 1) / 2; accum[(n + 1) * (numrho + 2) + r + 1]++; } } } } //printf("preangle1,preangle2:%d %d\n ",preangle1,preangle2); //找出数值最大的小格 int numbermax1 = 30, numbermax2 = 30; for (r = 0; r < numrho; r++)//angle1\angle2 ???? { for (n = 40; n < 70; n++) { int base = (n + 1) * (numrho + 2) + r + 1; if (accum[base] > numbermax1) { numbermax1 = accum[base]; angle1 = n; distance1 = cvRound(r - (numrho - 1)*0.5f); } } for (n = 110; n<160; n++) { int base = (n + 1) * (numrho + 2) + r + 1; if (accum[base] > numbermax2) { numbermax2 = accum[base]; angle2 = n; distance2 = cvRound(r - (numrho - 1)*0.5f); } } } //printf("angle1,angle2, distance1,distance2:%d %d %d %d\n",angle1, angle2,distance1,distance2); //if( distance1 || distance2 ) //{ if (angle1 == 0) { lineleft.pointbottom.x = 0; lineleft.pointbottom.y = 0; lineleft.pointtop.x = 0; lineleft.pointtop.y = 0; } if (angle2 == 0) { lineright.pointbottom.x = 0; lineright.pointbottom.y = 0; lineright.pointtop.x = 0; lineright.pointtop.y = 0; } //??????? if (angle1 < 90) { if ((lineleft.pointbottom.y = (int)(distance1 / tabSin[angle1])) > image->height)//此处分母tabSin[angle1]为零 { lineleft.pointbottom.x = (int)((distance1 - image->height * tabSin[angle1]) / tabCos[angle1]); lineleft.pointbottom.y = image->height; } else lineleft.pointbottom.x = 0; if ((lineleft.pointtop.x = (int)(distance1 / tabCos[angle1])) > image->width) { lineleft.pointtop.x = image->width; lineleft.pointtop.y = (int)((distance1 - image->width*tabCos[angle1]) / tabSin[angle1]); } else lineleft.pointtop.y = 0; } if (angle2 > 90 /* && angle2 < 180*/) { if ((lineright.pointtop.y = int(distance2 / tabSin[angle2])) < 0) { lineright.pointtop.y = 0; lineright.pointtop.x = int(distance2 / tabCos[angle2]); } else lineright.pointtop.x = 0; if (((lineright.pointbottom.x = (int)((distance2 - image->height *tabSin[angle2]) / tabCos[angle2])) > image->width)) { lineright.pointbottom.x = image->width; lineright.pointbottom.y = int((distance2 - image->width*tabCos[angle2]) / tabSin[angle2]); } else lineright.pointbottom.y = image->height; } predistance1 = distance1; preangle1 = angle1; predistance2 = distance2; preangle2 = angle2; return angle1; //} } //找出直线的相交点 CvPoint findmeetpoint(IplImage* image, float* tabSin, float *tabCos, int angleleft, int angleright) { //float tanA = tabCos[angleleft] / tabSin[angleleft]; //float tanB = tabCos[angleright] / tabSin[angleright] ; float tanA = -tabCos[angleleft] / tabSin[angleleft];//分母为零,赋值为1也不行 float tanB = -tabCos[angleright] / tabSin[angleright]; CvPoint pointmeet; pointmeet.x = (lineright.pointbottom.y - lineleft.pointbottom.y + lineleft.pointbottom.x*tanA - lineright.pointbottom.x*tanB) / (tanA - tanB); pointmeet.y = (pointmeet.x - lineleft.pointbottom.x)*tanA + lineleft.pointbottom.y; return pointmeet; } //判断出弯曲的方向,0代表没有弯曲，1代表左弯，2代表右弯 int finddirection(IplImage* image, float* tabSin, float *tabCos, int angleleft, int angleright) { int i = 0, j = 0; int i1 = 0, j1 = 0; int step = image->widthStep / sizeof(uchar); //imagestep为排列的图像行大小 uchar *data0 = (uchar *)image->imageData; //指向排列的图像数据 uchar *data1 = (uchar *)image->imageData; int numwhite = 0, numblack = 0; int num = 0; //float tanA = tabCos[angleleft] / tabSin[angleleft]; //float tanB = tabCos[angleright] / tabSin[angleright] ; float tanA = -tabCos[angleleft] / tabSin[angleleft]; float tanB = -tabCos[angleright] / tabSin[angleright]; pointmeet.x = 0; pointmeet.y = 0; pointmeet = findmeetpoint(image, tabSin, tabCos, angleleft, angleright); //找出直线与曲线的交点 //左车道 //偏离点的确定。 for (i = lineleft.pointbottom.y; i > pointmeet.y; i--) { j = float((i - lineleft.pointbottom.y)) / tanA + lineleft.pointbottom.x;//什么公式？？ if (data0[i*step + j] == 255)//???? { //printf( "pointmeet1:%f\n", (float)pointmeet.y ); pointtemp.x = j; pointtemp.y = i; numwhite++; } if (data0[i*step + j] != 255 && numwhite > 20) { pointsleft.push_back(pointtemp); numblack++; break; } if (numblack>3) pointsleft.push_back(pointtemp); } numwhite = 0; for (i = lineright.pointbottom.y; i > pointmeet.y; i--) { j = float((i - lineright.pointbottom.y)) / tanB + lineright.pointbottom.x; //printf("%f", data1[i*step]); if (data1[i*step + j] > 200) //200改大或改小都不行,>改成== { //printf("pointmeet2:%f\n", (int)pointmeet.y ); pointtemp.x = j; pointtemp.y = i; numwhite++; } if (data1[i*step + j] != 255 && numwhite>20) { pointsright.push_back(pointtemp); numblack++; break; } if (numblack>3) pointsright.push_back(pointtemp); } /////////////////////////////////////////////// if (pointsleft.size() == 0 || pointsright.size() == 0) { pointtemp.y = 0; pointtemp.x = 0; pointsright.clear(); pointsleft.clear(); pointsright.push_back(pointtemp); pointsleft.push_back(pointtemp); return 0; } //////////////////////////////////////////////////// //结合左右车道进行直线与曲线切点的校正 int tempy = (pointsleft.back().y<pointsright.back().y) ? pointsleft.back().y : pointsright.back().y; for (i = tempy; i<pointsleft.back().y; i++) { j = float((i - lineleft.point