finding Image shift

Question

Hi, How to find shift and rotation between same two images using programming languages vb.net or C++ or C#? Please help urgent

Answer 1

The problem you state is called motion detection (or motion compensation) and is one of the most important problems in image and video processing at the moment. No easy "here are ten lines of code that will do it" solution exists except for some really trivial cases.

Even your seemingly trivial case is quite a difficult one because a rotation by an unknown angle could cause slight pixel-by-pixel changes that can't be easily detected without specifically tailored algorithms used for motion detection.

Answer 2

There is no short answer. You could try to use free OpenCV library for finding relationship between two images.

Answer 3

If the images are very similar such that the camera is only slightly moved and rotated then the problem could be solved without using highly complex techniques. What I would do, in that case, is use a motion tracking algorithm to get the optical flow of the image sequence which is a "map" which approximates how a pixel has "moved" from image A to B. OpenCV which is indeed a very good library has functions that does this: CalcOpticalFlowLK and CalcOpticalFlowPyrLK.

The tricky bit is going from the optical flow to total rotation of the image. I would start by heavily low pass filter the optical flow to get a smoother map to work with. Then you need to use some logic to test if the image is only shifted or rotated. If it is only shifted then the entire map should be one "color", i.e. all flow vectors point in the same direction. If there has been a rotation then the vectors will point in different direction depending on the rotation.

If the input images are not as nice as the above method requires, then I would look into feature descriptors to find how a specific object in the first image is located within the second. This will however be much harder.

Answer 4

The two operations, rotation and translation can be determined in either order. It's far easier to first detect rotation, because you can then compensate for that. Once both images are oriented the same, the translation becomes a matter of simmple correlation.

Finding the relative rotation of an image is best done by determining the local gradients. For every neighborhood (e.g. 3x3 pixels), treat the greyvalue as a function z(x,y), fit a plane through the 9 pixels, and determine the slope or gradient of that plane. Now average the gradient you found over the entire image, or at least the center of it. Your two images will produce different averages. Part of that is because for non-90 degree rotations the images won't overlap fully, but in general the difference in average gradients is the rotation between the two.

Once you've rotated back one image, you can determine a correlation. This is a fairly standard operation; you're essentially determining for each possible offset how well the two images overlap. This will give you an estimate for the shift.

Once you've got both, you can refine your rotation angle estimate by rotating back the translation, shifting the second image, and determining the average gradient only over the pixels common to both images.

Answer 5

If the images are exactly the same, it should be fairly easy to extract some feature points - for example using SIFT - and match the features of both images. You can then use any two of the matching features to find the rotation and translation. The translation is just the difference between two matching feature points. The you compensate for the translation in one image and get the rotation angle as the angle formed by the three remaining points.