How to find one image inside of another?

Solution 1:

Here's a quick sample but it is slow take around 4-6 seconds, but it does exactly what you looking for and i know this post is old but if anyone else visiting this post recently you can look this thing you need .NET AForge namespace or framework google it and install it include AForge name space in your project and that's it it finds the pictiure with another and gives out the coordinates.

System.Drawing.Bitmap sourceImage = (Bitmap)Bitmap.FromFile(@"C:\SavedBMPs\1.jpg");
            System.Drawing.Bitmap template = (Bitmap)Bitmap.FromFile(@"C:\SavedBMPs\2.jpg");
            // create template matching algorithm's instance
            // (set similarity threshold to 92.1%)

           ExhaustiveTemplateMatching tm = new ExhaustiveTemplateMatching(0.921f);
                // find all matchings with specified above similarity

                TemplateMatch[] matchings = tm.ProcessImage(sourceImage, template);
                // highlight found matchings

           BitmapData data = sourceImage.LockBits(
                new Rectangle(0, 0, sourceImage.Width, sourceImage.Height),
                ImageLockMode.ReadWrite, sourceImage.PixelFormat);
            foreach (TemplateMatch m in matchings)
            {

                    Drawing.Rectangle(data, m.Rectangle, Color.White);

                MessageBox.Show(m.Rectangle.Location.ToString());
                // do something else with matching
            }
            sourceImage.UnlockBits(data);

Solution 2:

1. So is there any warping of ImageB in ImageA?
2. How "exact" are the images, as in, pixel-for-pixel they will be the same?
3. How much computational power do you have for this?

If the answers to the first two questions are No and Yes, then you have a simple problem. It also helps to know the answer to Q3.

Update:

The basic idea's this: instead of matching a window around every pixel in imageB with every pixel in imageA and checking the correlation, let's identify points of interest (or features) in both images which will be trackable. So it looks like corners are really trackable since the area around it is kinda similar (not going into details) - hence, let's find some really strong corners in both images and search for corners which look most similar.

This reduces the problem of searching every pixel in B with A to searching for, say, 500 corners in B with a 1000 corners in A (or something like that) - much faster.

And the awesome thing is you have several such corner detectors at your disposal in OpenCV. If you don't feel using emguCV (C# varriant), then use the FAST detector to find matching corners and thus locate multiple features between your images. Once you have that, you can find the location of the top-left corner of the image.

Solution 3:

If image B is an exact subset of image A (meaning, the pixel values are exactly the same), this is not an image processing problem, it's just string matching in 2D. In 99% of the cases, taking a line form the middle of B and matching it against each line of A will do what you want, and super fast &mdhas; I guess C# has a function for that. After you get your matches (normally, a few of them), just check the whole of B against the appropriate part of A.

The only problem I can see with this is that in some cases you can get too many matches. E.g. if A is your desktop, B is an icon, and you are unlucky enough to pick a line in B consisting of background only. This problem is easy to solve (you have to choose lines from B a bit more carefully), but this depends on the specifics of your problem.