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Lane_detetor.cpp
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Lane_detetor.cpp
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#include <iostream>
#include "cv.hpp"
using namespace cv;
using namespace std;
int main()
{
VideoCapture cap("lane.avi");
Mat src, gray, blur, sobel, canny, grad_x, grad_y, roi, result, masked, eroded;
double fps = cap.get(CAP_PROP_FPS);
float rho, theta, theta_sum, theta_sum2, theta_mean, theta_mean2, a, b, x0, y0;
float rho_sum, rho_sum2, rho_mean, rho_mean2;
int cnt = 0, cnt2 = 0;
theta_sum = 0, theta_sum2 = 0;
rho_sum = 0, rho_sum2 = 0;
int delay = 1000 / (int)fps;
Point p1, p2;
vector<Vec2f> lines, lines2;
cap >> src;
Rect rect(src.size().width / 2 - 220, src.size().height / 2 - 50, 500, 180);
Rect rect_inner(src.size().width / 2 - 70, src.size().height / 2, 200, 300),
rect_inner1(src.size().width / 2 - 230, src.size().height / 2-50, 100, 100),
rect_inner2(src.size().width / 2 + 180, src.size().height / 2 - 70, 100, 100);
roi = src(rect); //Set ROI
Mat mask = Mat::zeros(src.size(), src.type()); //Mask to isolate ROI
cvtColor(mask, mask, CV_BGR2GRAY);
rectangle(mask, rect, 255, CV_FILLED, 8); //Drawing a rectangular mask
rectangle(mask, rect_inner, 0, CV_FILLED, 8); //Rectangular mask for center of the road
rectangle(mask, rect_inner1, 0, CV_FILLED, 8); //Rectangular mask for lefttop of the road
rectangle(mask, rect_inner2, 0, CV_FILLED, 8); //Rectangular mask for righttop of the road
//imshow("hi", mask);
while (1)
{
if (!cap.read(src))
{
cout << "Input video error!" << endl;
break;
}
if (src.empty())
{
cout << "Input frame is empty!" << endl;
break;
}
cvtColor(src, gray, CV_BGR2GRAY);
threshold(gray, result, 150, 255, THRESH_BINARY | THRESH_OTSU); //Otsu's thresholding
Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3));
erode(result, eroded, kernel); //Erode the image with the 'kernel' - structuring element
//imshow("ERODED", eroded);
Canny(eroded, canny, 50, 180, 5); //Edge detection & localization
bitwise_and(canny, mask, masked); //Use bitwise_and to mask out the rest outside of ROI
HoughLines(masked, lines, 1, CV_PI / 180, 50, 0, 0, 130 * (CV_PI/180), 145 * (CV_PI/180)); //Right lane (white-dotted lane)
HoughLines(masked, lines2, 1, CV_PI / 180, 70, 0, 0, 30 * (CV_PI / 180), 55 * (CV_PI / 180)); //Left lane (yellow lane)
for (int i = 0; i < lines.size(); i++) //Get the sum of rho and theta for the right lane
{
rho_sum += lines[i][0];
theta_sum += lines[i][1];
cnt++;
}
for (int j = 0; j < lines2.size(); j++) //Get the sum of rho and theta for the left lane
{
rho_sum2 += lines2[j][0];
theta_sum2 += lines2[j][1];
cnt2++;
}
rho_mean = rho_sum / cnt; //Calculate the mean of the rho
rho_mean2 = rho_sum2 / cnt2;
theta_mean = theta_sum / cnt; //Calculate the mean of the theta
theta_mean2 = theta_sum2 / cnt2;
cout << "theta_right: " << (theta_mean*180) / CV_PI<< endl << "theta_left " << (theta_mean2*180) / CV_PI << endl;
for (int i = 0; i < lines.size(); i++) //Right lane (white-dotted lane)
{
rho = lines[i][0];
theta = lines[i][1];
a = cos(theta_mean);
b = sin(theta_mean);
x0 = a * rho_mean;
y0 = b * rho_mean;
p1 = Point(cvRound(x0 + 1000 * (-b)), cvRound(y0 + 1000 * a));
p2 = Point(cvRound(x0 - 10000 * (-b)), cvRound(y0 - 10000 * a));
if (theta_mean < 0)
break;
else
{
line(src, p1, p2, Scalar(0, 0, 255), 8, 8);
cout << (theta_mean * 180) / CV_PI << endl;
}
}
for (int i = 1; i < lines2.size(); i++) //Left lane (yellow lane)
{
rho = lines2[i][0];
theta = lines2[i][1];
a = cos(theta_mean2);
b = sin(theta_mean2);
x0 = a * rho_mean2;
y0 = b * rho_mean2;
p1 = Point(cvRound(x0 + 1000 * (-b)), cvRound(y0 + 1000 * a));
p2 = Point(cvRound(x0 - 1000 * (-b)), cvRound(y0 - 1000 * a));
if (theta_mean2 < 0)
break;
else
{
line(src, p1, p2, Scalar(0, 0, 255), 8, 8);
cout << (theta_mean2 * 180) / CV_PI << endl;
}
}
//imshow("CANNY_EDGE", canny);
imshow("ORIGINAL", src);
//imshow("BLURRED", blur);
//imshow("ROI_BINARY", masked);
imshow("ROI", roi);
waitKey(delay/10);
}
}