IplImage* greyImage     = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);
IplImage* colourImage   = cvCreateImage( imgSize, IPL_DEPTH_8U,3);
IplImage* movingAverage = cvCreateImage( imgSize, IPL_DEPTH_32F, 3);
IplImage* difference    = cvCreateImage( imgSize, IPL_DEPTH_8U, 3);
IplImage* temp          = cvCreateImage( imgSize, IPL_DEPTH_8U, 3);
// Create a window
cvNamedWindow( "Image", 1 ); // creation of a visualisation window
cvNamedWindow( "BG", 1 ); // creation of a visualisation window
cvNamedWindow( "Source", 1 ); // creation of a visualisation wind

int key=-1;
int flag=0;
while(key != 'q')
  {
    // Take a picture
    phil.grabImage();

    // Copy from the camera buffer to the OpenCV image buffer
    cvSetImageData(greyImage,  phil.getGreyPointer(),imgSize.width*1);
    cvSetImageData(colourImage,phil.getColourPointer(),imgSize.width*3);

    if (flag==0)
    {
        cvConvertScale(colourImage,movingAverage,1.0,0.0);
        flag=1;
    }
    else
    {
        cvRunningAvg( colourImage, movingAverage, 0.015 ,NULL);
    }

    cvConvertScale(movingAverage,temp,1.0,0.0);
    cvShowImage("BG",temp);
    cvAbsDiff(colourImage,temp,difference);
    cvThreshold(difference,difference,50,255,CV_THRESH_BINARY);
    cvCvtColor( difference,greyImage, CV_BGR2GRAY );

    // Display the image
    cvShowImage("Source",colourImage);
    cvShowImage("Image",greyImage);

    // Capture a key press, but more importantly allow the
    // window to refresh
    key = cvWaitKey(1);  
  }    

// Allocate space for image
IplImage* image = cvCreateImage( imgSize, IPL_DEPTH_8U, 1);
IplImage* output = cvCreateImage( imgSize, IPL_DEPTH_8U, 3);
IplImage * eigImage  = cvCreateImage( imgSize, IPL_DEPTH_32F, 1);
IplImage * tempImage = cvCreateImage( imgSize, IPL_DEPTH_32F, 1);

int cornerCount=20;
CvPoint2D32f corners[cornerCount];

// Create a window
cvNamedWindow( "Image", 1 ); // Source image
cvNamedWindow( "Output", 1 ); // working window
int key=-1;
while(key != 'q')
  {
    // Take a picture
    phil.grabImage();

    // Copy from the camera buffer to the OpenCV image buffer
    cvSetImageData(image,phil.getGreyPointer(),imgSize.width);
    cvSetImageData(output,phil.getColourPointer(),imgSize.width*3);
    cvSmooth(image,image,CV_GAUSSIAN,7,7);
    cvGoodFeaturesToTrack(image,eigImage,tempImage,corners,&cornerCount,0.001,50);
    for (int i=0;i<cornerCount;i++)
    {
        cvCircle(output,cvPoint(corners[i].x,corners[i].y),10,CV_RGB(255,0,0),3);
    }
    cvShowImage("Output",output);
    // Capture a key press, but more importantly allow the
    // window to refresh
    key = cvWaitKey(1);
  }  

#include <cv.h>
#include <highgui.h>
#include <cstdio>
#include <cmath>
#include <cstring>
#include <PhilipsCamera.h>

using namespace std;

int thresh = 50;
IplImage* img = 0;
IplImage* img0 = 0;
CvMemStorage* storage = 0;
CvPoint pt[4];

// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2 
double angle( CvPoint* pt1, CvPoint* pt2, CvPoint* pt0 )
{
  double dx1 = pt1->x - pt0->x;
  double dy1 = pt1->y - pt0->y;
  double dx2 = pt2->x - pt0->x;
  double dy2 = pt2->y - pt0->y;
  return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}

// returns sequence of squares detected on the image.
// the sequence is stored in the specified memory storage
CvSeq* findSquares4( IplImage* img, CvMemStorage* storage )
{
  CvSeq* contours;
  int i, c, l, N = 11;
  CvSize sz = cvSize( img->width & -2, img->height & -2 );
  IplImage* timg = cvCloneImage( img ); // make a copy of input image
  IplImage* gray = cvCreateImage( sz, 8, 1 ); 
  IplImage* pyr = cvCreateImage( cvSize(sz.width/2, sz.height/2), 8, 3 );
  IplImage* tgray;
  CvSeq* result;
  double s, t;
  // create empty sequence that will contain points -
  // 4 points per square (the square's vertices)
  CvSeq* squares = cvCreateSeq( 0, sizeof(CvSeq), sizeof(CvPoint), storage );

  // select the maximum ROI in the image
  // with the width and height divisible by 2
  cvSetImageROI( timg, cvRect( 0, 0, sz.width, sz.height ));

  // down-scale and upscale the image to filter out the noise
  cvPyrDown( timg, pyr, 7 );
  cvPyrUp( pyr, timg, 7 );
  tgray = cvCreateImage( sz, 8, 1 );

  // find squares in every color plane of the image
  for( c = 0; c < 3; c++ )
    {
      // extract the c-th color plane
      cvSetImageCOI( timg, c+1 );
      cvCopy( timg, tgray, 0 );

      // try several threshold levels
      for( l = 0; l < N; l++ )
        {
      // hack: use Canny instead of zero threshold level.
      // Canny helps to catch squares with gradient shading   
      if( l == 0 )
            {
          // apply Canny. Take the upper threshold from slider
          // and set the lower to 0 (which forces edges merging) 
          cvCanny( tgray, gray, 0, thresh, 5 );
          // dilate canny output to remove potential
          // holes between edge segments 
          cvDilate( gray, gray, 0, 1 );
            }
      else
            {
          // apply threshold if l!=0:
          //     tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
          cvThreshold( tgray, gray, (l+1)*255/N, 255, CV_THRESH_BINARY );
            }

      // find contours and store them all as a list
      cvFindContours( gray, storage, &contours, sizeof(CvContour),
              CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE );

      // test each contour
      while( contours )
            {
          // approximate contour with accuracy proportional
          // to the contour perimeter
          result = cvApproxPoly( contours, sizeof(CvContour), storage,
                     CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0 );
          // square contours should have 4 vertices after approximation
          // relatively large area (to filter out noisy contours)
          // and be convex.
          // Note: absolute value of an area is used because
          // area may be positive or negative - in accordance with the
          // contour orientation
          if( result->total == 4 &&
          fabs(cvContourArea(result,CV_WHOLE_SEQ)) > 1000 &&
          cvCheckContourConvexity(result) )
                {
          s = 0;

          for( i = 0; i < 5; i++ )
                    {
              // find minimum angle between joint
              // edges (maximum of cosine)
              if( i >= 2 )
                        {
              t = fabs(angle(
                     (CvPoint*)cvGetSeqElem( result, i, 0 ),
                     (CvPoint*)cvGetSeqElem( result, i-2, 0 ),
                     (CvPoint*)cvGetSeqElem( result, i-1, 0 )));
              s = s > t ? s : t;
                        }
                    }

          // if cosines of all angles are small
          // (all angles are ~90 degree) then write quandrange
          // vertices to resultant sequence 
          if( s < 0.1 )
            for( i = 0; i < 4; i++ )
              cvSeqPush( squares,
                 (CvPoint*)cvGetSeqElem( result, i, 0 ));
                }

          // take the next contour
          contours = contours->h_next;
            }
        }
    }

  // release all the temporary images
  cvReleaseImage( &gray );
  cvReleaseImage( &pyr );
  cvReleaseImage( &tgray );
  cvReleaseImage( &timg );

  return squares;
}


// the function draws all the squares in the image
void drawSquares( IplImage* img, CvSeq* squares )
{
  CvSeqReader reader;
  IplImage* cpy = cvCloneImage( img );
  int i;

  // initialize reader of the sequence
  cvStartReadSeq( squares, &reader, 0 );

  // read 4 sequence elements at a time (all vertices of a square)
  for( i = 0; i < squares->total; i += 4 )
    {
      CvPoint* rect = pt;
      int count = 4;

      // read 4 vertices
      memcpy( pt, reader.ptr, squares->elem_size );
      CV_NEXT_SEQ_ELEM( squares->elem_size, reader );
      memcpy( pt + 1, reader.ptr, squares->elem_size );
      CV_NEXT_SEQ_ELEM( squares->elem_size, reader );
      memcpy( pt + 2, reader.ptr, squares->elem_size );
      CV_NEXT_SEQ_ELEM( squares->elem_size, reader );
      memcpy( pt + 3, reader.ptr, squares->elem_size );
      CV_NEXT_SEQ_ELEM( squares->elem_size, reader );

      // draw the square as a closed polyline 
      cvPolyLine( cpy, &rect, &count, 1, 1, CV_RGB(255,0,0), 3, 8 );
    }

  // show the resultant image
  cvShowImage("image",cpy);
  cvReleaseImage( &cpy );
}


void on_trackbar( int a )
{
  if( img )
    drawSquares( img, findSquares4( img, storage ) );
}



int main(int argc, char** argv)
{
  PhilipsCamera phil;             // Declare the camera object 
  phil.openDevice("/dev/video1"); // ...and open the device
  CvSize imgSize;                 // A CvSize structure to hold the dimensions
  imgSize.width = 640; 
  imgSize.height = 480;

  // Set the camera to the right resolution
  phil.setResolution(imgSize.width,imgSize.height);
  img = cvCreateImage( imgSize, IPL_DEPTH_8U, 3);
  int i;
  // create memory storage that will contain all the dynamic data
  storage = cvCreateMemStorage(0);
  // create window with name "image"
  cvNamedWindow( "image", 1 );
  // create trackbar (slider) with parent "image" and set callback
  // (the slider regulates upper threshold, passed to Canny edge detector) 
  cvCreateTrackbar( "thresh1", "image", &thresh, 1000, on_trackbar );
  int key;
  while(key!='q')
    {
      // Take a picture
      phil.grabImage();

      // Copy from the camera buffer to the OpenCV image buffer
      cvSetImageData(img,phil.getColourPointer(),imgSize.width*3);

      // force the image processing
      on_trackbar(0);
      // wait for key.
      // Also the function cvWaitKey takes care of event processing
      key=cvWaitKey(1);
      // release image
      //cvReleaseImage( &img );
      // clear memory storage - reset free space position
      cvClearMemStorage( storage );
    }

  cvDestroyWindow("image");

  return 0;
}