Find known sub image in larger image

Question

Does anyone know of an algorithm (or search terms / descriptions) to locate a known image within a larger image?

e.g.

I have an image of a s

Answer 1

Your don't need fuzzy as in "neural network" because (as I understand) you don't have rotation, tilts or similar. If OS display differences are the only modifications the difference should be minimal. So WernerVanBelle's paper is nice but not really necessary and MrFooz's code works - but is terribly innefficient (O(width * height * patter_width * pattern_height)!).

The best algorithm I can think of is the Boyer-Moore algorithm for string searching, modified to allow 2 dimensional searches. http://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm

Instead of one displacement you will have to store a pair of displacements dx and dy for each color. When checking a pixel you move only in the x direction x = x + dx and store only the minimum of the dy's DY = min(DY, dy) to set the new y value after a whole line has been tested (ie x > width).

Creating a table for all possible colors probably is prohibitve due to the imense number of possible colors, so either use a map to store the rules (and default to the pattern dimensions if a color is not inside the map) or create tables for each color seperately and set dx = max(dx(red), dx(green), dx(blue)) - which is only an approximation but removes the overhead of a map.

In the preprocessing of the bad-character rule, you can account for small deviations of colors by spreading rules from all colors to their "neighbouring" colors (however you wish to define neighbouring).