Phase 1: Image Warping

1- Background Information: 

-Why we need Image Warping?

To project the image properly on the display while moving, we need to calculate the transformation matrix that's being applied to the image before projecting it in order to fit the movement of the display.

- How image warping is implemented?

As the display moves new coordinates are given to the IRLEDS , so using these new coordinates (destination) and the corners of the image (source), we can estimate the homography matrix.

The homography matrix (transformation) is applied to the image and we get the warped image to be projected. This is all done by openCV functions :
-“cvFindHomography”: which computes the homography matrix using source & destination points (IRLEDS coordinates).
-“cvWarpPerspective”: This applies the transformation calculated above to the image to be projected.

 

2- Into the details:


- Transformations Taxonomy:
There are  4 types of transformations:

 the following picture shows the effect of applying different transformation types on an image

and since that our display moves in 8 degrees of  freedom, so we used the Homography matrix.

dof: (forward/backward, up/down, left/right (translation) combined with rotation about three perpendicular axes (pitch, yaw, roll))

for more details abt the projective transformation see this ppt.


- Forward Warping VS Inverse Warping
This ppt explains the concept of forward & inverse warping,
remeber if u're using the inverse warping you should use the inverse of the homography matrix not the homography matrix itself 
 

3- C# Code: 

This code uses openCV 1.1,  this book explains the openCv fns used below

also we use Emgu .Net Wrapper and this is its Wiki for documentation abt it

This's just a simple test code, to warp an image from srcp to dstp

private void warping()
        {
           
            imageBox2.Image=src;

            float[,] srcp = { { 0, 0 }, { src.Width-1, 0 }, { 0, src.Height-1 }, { src.Width-1, src.Height-1} };
            float[,] dstp = { { src.Width * 0.05f, src.Height * 0.33f }, { src.Width * 0.9f, src.Height * 0.25f }, { src.Width * 0.2f, src.Height * 0.7f }, { src.Width * 0.8f, src.Height * 0.9f } };
            float[,] homog = new float[3, 3];

            Matrix srcpm = new Matrix(srcp);
            Matrix dstpm = new Matrix(dstp);
            Matrix homogm = new Matrix(homog);
            IntPtr n = new IntPtr();

            CvInvoke.cvFindHomography(srcpm.Ptr, dstpm.Ptr, homogm.Ptr, Emgu.CV.CvEnum.HOMOGRAPHY_METHOD.DEFAULT, 0, n);
            src= src.WarpPerspective(homogm, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC, Emgu.CV.CvEnum.WARP.CV_WARP_INVERSE_MAP, new Bgr(Color.White));
            imageBox1.Image = src;
        }