Search for a pattern in an image

I have an image and a template. I am trying to find out if a pattern exists in the image, and if so, where are its instances inside the image. Something like these images:

http://www-cgrl.cs.mcgill.ca/~godfried/teaching/cg-projects/98/normand/ex1-model-bit.gif http://www-cgrl.cs.mcgill.ca/~godfried /teaching/cg-projects/98/normand/ex1-image-bit.gif

This will be the result: http://www-cgrl.cs.mcgill.ca/~godfried/teaching/cg-projects/98/normand/sc1-match.gif

These images are taken from this page: http://www-cgrl.cs.mcgill.ca/~godfried/teaching/cg-projects/98/normand/main.html There is a link to the Rucklidge algorithm, but I did not find any information about this algorithm.

I do not need to rotate more than 15 degrees or scale more than 20% (larger or smaller). What would be the best way to do this?

* Edit: * I have a list of black pixels that form the edges of the image, and another list of pixels that form the pattern. I'm just looking for an easy way to find the best (x, y) offset for the list of pixels in the image of the template so that they are as close as possible to the pixels that form the image. Some tolerance would be good to allow a few percent scaling or a few degrees of rotation, but nothing radical.

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, , http://www.cs.cornell.edu/vision/hausdorff/hausmatch.html, , , , , .

Rucklidge , , " " (International Journal of Computer Vision, vol 24 issue 3, Sept./Oct. 1997) " ", Springer LNCS № 1173). , , Google. , , (, ), , .

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  • Hausdorff_distance(region, your_template)
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