c/c++语言开发共享C++ OpenCV实战之车道检测

目录

• 前言
• 一、获取车道roi区域
• 二、车道检测
• 1.灰度、阈值
• 2.获取非零像素点
• 3.绘制车道线
• 总结

void getroi(mat src, mat &image)  {      mat mask = mat::zeros(src.size(), src.type());        int width = src.cols;      int height = src.rows;        //获取车道roi区域，只对该部分进行处理      vector<point>pts;      point pta((width / 8) * 2, (height / 20) * 19);      point ptb((width / 8) * 2, (height / 8) * 7);      point ptc((width / 10) * 4, (height / 5) * 3);      point ptd((width / 10) * 5, (height / 5) * 3);      point pte((width / 8) * 7, (height / 8) * 7);      point ptf((width / 8) * 7, (height / 20) * 19);      pts = { pta ,ptb,ptc,ptd,pte, ptf };        fillpoly(mask, pts, scalar::all(255));      src.copyto(image, mask);    }

	mat gray;  	cvtcolor(image, gray, color_bgr2gray);    	mat thresh;  	threshold(gray, thresh, 180, 255, thresh_binary);  	imshow("thresh", thresh);  

	vector<point>left_line;  	vector<point>right_line;    	for (int i = 0; i < thresh.cols / 2; i++)  	{  		for (int j = 0; j < thresh.rows; j++)  		{  			if (thresh.at<uchar>(j, i) == 255)  			{  				left_line.push_back(point(i, j));    			}  		}  	}    	for (int i = thresh.cols / 2; i < thresh.cols; i++)  	{  		for (int j = 0; j < thresh.rows; j++)  		{  			if (thresh.at<uchar>(j, i) == 255)  			{  				right_line.push_back(point(i, j));  			}  		}  	}  

	if (left_line.size() > 0 && right_line.size() > 0)  	{  		point b_l = (left_line[0]);  		point t_l = (left_line[left_line.size() - 1]);  		point t_r = (right_line[0]);  		point b_r = (right_line[right_line.size() - 1]);    		circle(src, b_l, 10, scalar(0, 0, 255), -1);  		circle(src, t_l, 10, scalar(0, 255, 0), -1);  		circle(src, t_r, 10, scalar(255, 0, 0), -1);  		circle(src, b_r, 10, scalar(0, 255, 255), -1);    		line(src, point(b_l), point(t_l), scalar(0, 255, 0), 10);  		line(src, point(t_r), point(b_r), scalar(0, 255, 0), 10);    		vector<point>pts;  		pts = { b_l ,t_l ,t_r ,b_r };  		fillpoly(src, pts, scalar(133, 230, 238));  	}