Detect rectangular using Hough Transform

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I am trying to detect the biggest rectangulare shape in the image (TV screen detection) but first I want to detect all rectangular shapes using Hough Lines (findCounturs didn't work so well for my case). I've managed to extract HoughLines and all of the corners, but how can I extract rectangulars from this? (I'm new to OpenCV and I want to learn)

here is my code:

        Mat src = imread("image.jpg"):
        cv::Mat bw;
        src.copyTo(bw);
        cv::cvtColor(src, bw, CV_BGR2GRAY);
        cv::blur(bw, bw, cv::Size(3, 3));
        cv::Canny(bw, bw, 100, 100, 3);

        std::vector<cv::Vec4i> lines;
        cv::HoughLinesP(bw, lines, 1, CV_PI/180, 70, 30, 10);

        // Expand the lines
        for (int i = 0; i < lines.size(); i++)
        {
                cv::Vec4i v = lines[i];
                lines[i][0] = 0;
                lines[i][1] = ((float)v[1] - v[3]) / (v[0] - v[2]) * -v[0] + v[1]; 
                lines[i][2] = src.cols; 
                lines[i][3] = ((float)v[1] - v[3]) / (v[0] - v[2]) * (src.cols - v[2]) + v[3];
        }

        std::vector<cv::Point2f> corners;
        for (int i = 0; i < lines.size(); i++)
        {
                for (int j = i+1; j < lines.size(); j++)
                {
                        cv::Point2f pt = computeIntersect(lines[i], lines[j]);
                        if (pt.x >= 0 && pt.y >= 0)
                                corners.push_back(pt);
                }
        }

and the used function above:

Point2f computeIntersect(cv::Vec4i a, 
                             cv::Vec4i b)
{
        int x1 = a[0], y1 = a[1], x2 = a[2], y2 = a[3], x3 = b[0], y3 = b[1], x4 = b[2], y4 = b[3];
        float denom;

        if (float d = ((float)(x1 - x2) * (y3 - y4)) - ((y1 - y2) * (x3 - x4)))
        {
                cv::Point2f pt;
                pt.x = ((x1 * y2 - y1 * x2) * (x3 - x4) - (x1 - x2) * (x3 * y4 - y3 * x4)) / d;
                pt.y = ((x1 * y2 - y1 * x2) * (y3 - y4) - (y1 - y2) * (x3 * y4 - y3 * x4)) / d;
                return pt;
        }
        else
                return cv::Point2f(-1, -1);
}