How can I fit and then overlay 2 images which have different resolution ?

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@theodore thank you for your time, patience and kindness. It is difficult to do what I need to do :\ I need to do something kike that : link text . This was made with imagemagick. However, the images were with lower resolution, and the mesh is different. I think with this image you are able to figure out what I need to do. I will see the algorithm.

I do not think that it is that hard, what you want to do. More or less you have the material you need. You just need to mix them in the proper way. Unfortunately, I do not have that much free time at the moment otherwise I could help you with some code as well.

@LBerger , Yes, as I mentioned there are different images, with similarities on shape. I want to do something like this: http://i.stack.imgur.com/fyixS.jpg

@LBerger , @theodore , @sturkmen , any brillant idea?

@LBerger the image with the mesh is a render created using matplotlib. From this image, using potrace I got this vector, which allows me get the mesh using trimesh pythom modulel stl, using matplotlib to render, I got the mesh that you've seen .

This is not easier or trivial :\

@LBerger it is not a really alighment .If you look here . you'd notice the mesh (at red) it is the internal countour of the overlaied picture. This example it's with other images and it was done with imagemagick.

In your example you have two images R and B(red and black). I think you want to minimize |R(x,y)-B(ax+x0,by+y0)]^2 relative to unknown a,b,x0,y0

@LBerger I think I'm getting what your telling. However, I don't think if it solves the aligment problem. I was thinking about the problem. If at the primary image (the one with the boundaries, which later is used to generate the mesh) it is added points (for instance, holes center), later at the mesh image, could they be matched ? If the points are the same in all images (all the images have holes center) could it solve the problem? Like a plot layer to guide the others. I don't know how to do it, I'm just thinking from the concept point of view.

Something like this : holes with center

both in you mesh image and in you original image there are some parts that are visible in both images, e.g. some squares/circles. Why not to use these in order to extract the four points (minimum) to extract the homography and align your images, as I said in my answer?

@theodore I think that's what I'm trying to do. Do you think this https://dl.dropboxusercontent.com/u/7... , I'm trying to isolate the same shapes on this image without success. After matching the shapes, what I should do? Find the same shapes on the layers images?

yes you need to extract corresponding matching points from both images, then you just feed them in the findHomography() function and you will get the transformation matrix to use it with wrapPerspective() function. See the links in my answer.

@theodore thx for answering. I've got a doubt. Do I need to match the points into the mesh image and then here ? On the mesh layer I've got another problem. I've a column of white pixels. How can I get rid off it? mesh image

@theodore In another words. I've got the image which is the source of the mesh, the mesh and layertohavemesh . I want to get something like this . I've found the centers of the 1st image . As I've said the mesh image as a problem, it was a column of white pixels from the upper left corner. Do I need homography on everything? How many points? The msh image and the original image from the mesh are equal. But the layer image not.Th mesh overlays some holes. Sorry; but there is a lot of information.

ok you have the points from the 1st image (you need at least 4, the merrier the better) put them in a vector<Point2f> pts_src. Now find the corresponding points in the layer image, put them in a vector<Point2f> pts_dst and now feed both vectors to the homography like that: Mat h = findHomography(pts_src, pts_dst) now you have the transformation that you need.

But they aren't the same. They would be similar. Sorry, probably I'm doing some mess.

what do you mean by they aren't the same?

If look here The holes of the mesh have different sizes of the layer. THe layer has larger countours, which is true

@theodore did you understand what my problem is? I think in a simple chat i could explain easily

try to use then points that would be more robust to changes, like the center of the circle. You also try to use the centers of the mass (look at hu momments and contours) of your boxes. You will always have some error if your points are not an exact much. The point is to find the best case with the less error. I would suggest first to try what I told you in practice and see that it works. Then you can transfer the problem on how to find the best matched points.

@theodore I agree with you. I was thinking if it would be better create at source image (the one which I use to generate the mesh) 3 or 4 points as guides, and then plot them on the mesh with the transformation and them draw them on the layer.