Detecting lines using proabilistic hough transform

We use Canny algorithm to create a binary image and then use the HoughLinesP function detects line in binary image.

First we take the bird eye view image of straight labe for processing.

When the HoughLinesP is applied we get following resulting lines:

Then we take a curved lane image

When the HoughLinesP is applied we get following resulting lines:

Here is the code.

int hough(const char *input_path, const char *output_path)
{
    Mat src_o, src, dst;
    src_o = imread(input_path);

    cvtColor(src_o, src, CV_BGR2GRAY );

    Canny(src, dst, 200, 255, 3 );

    vector lines;
    HoughLinesP(dst, lines, 1, CV_PI/180, 20, 10, 20 );

    std::map  candidate;

    for( size_t i = 0; i < lines.size(); i++ )
    {
        line( src_o, Point(lines[i][0], lines[i][1]),
              Point(lines[i][2], lines[i][3]), Scalar(0,0,255), 3, 8 );
    }

    imwrite(output_path, src_o);

    return 0;
}

Next step is to take the lines and calculate the lane midpoint.