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how to prune lines detected by houghtransformp ?

I am trying to detect quadrilateral and going to do a perspective correction based on http://opencv-code.com/tutorials/automatic-perspective-correction-for-quadrilateral-objects/ by using probabilistic hough transform.

I only need 4 lines, but i ended up with other things (as you can see in the picture)

it's on purpose that i take the object of interest with other square environment ( to see if my program is adaptive)

i tried to play with the threshold and other parameter but these 2 images are the best that i can end up with.

can anyone help me to prune other lines except the 4 lines that i need (the ones that make a quadrilateral) thanks.

image description

    int main()
{
//initialize the mat and variables
cv::Mat bw,rsz,roi,circleroi,result,dst,cannyimg;
int t1min =109;
//we want to adjust the size to 800x600
Size size(800,600); //the dst image size,e.g.800x600

//load the image
    cv::Mat src = cv::imread("D:\\image\\perspective.jpg");
    if (src.empty())
    return -1;

//create windows
    cvNamedWindow( "houghlinep", CV_WINDOW_AUTOSIZE );

while(1)
    {
    //create trackbars
        char TrackbarName1[50]="t1min";

        cvCreateTrackbar(TrackbarName1, "houghlinep", &t1min, 260 , NULL );
        if (t1min<=10)
            t1min=10;
    //resize image
    resize(src,rsz,size);
    //adjust the image boundary
    roi = rsz(cv::Range(110,560),cv::Range(70,685));
    //make the image grayscale to make it easier to canny   
    cv::cvtColor(roi, bw, CV_BGR2GRAY);
    //blur it to make it easier to canny
    cv::blur(bw, bw, cv::Size(2,2));
    //edge detect with canny operator
    cv::Canny(bw, dst, 50,100, 3);
    //copy the result to cannyimg
    dst.copyTo(cannyimg);

    //make lines object
    vector<Vec4i> lines;
    //use houghlinesp to dst
    HoughLinesP(dst, lines, 1, CV_PI/180,t1min, 140, 80 );
    //illustrate the line on the black n white image

    char count=1;
      for( size_t i = 0; i < lines.size(); i++ )
      {
        Vec4i l = lines[i];
        line(bw, Point(l[0], l[1]), Point(l[2], l[3]), CV_RGB(0,255,255), 1, CV_AA);

      }

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



      //show the images

    cv::imshow("canny",cannyimg);
    cv::imshow("houghlinep",bw);
    cv::imshow("yeah",roi);


    if(t1min=t1min) cvWaitKey(0);

   if( (cvWaitKey(10) & 255) == 27 ) break;
   cvReleaseFileStorage;
}
return 1;


}