Chris Greening, the developer of iPhone Sudoku Grab, explains how it works. I find this section the most interesting:
One of the things that makes recognizing Sudoku puzzles an easier task than most image processing/recognition problem is that it is a highly constrained problem – a standard Sudoku puzzle is going to be a square grid and it will only contain the printed numbers 1-9. These two points are very important. The first point – it’s a square grid tells us what shape a puzzle is and what we should be looking for in an image. The second point – it will only contain the printed numbers 1-9 tells us that we aren’t going to need a sophisticated OCR system. When we look at the problem there’s nothing that jumps out and says “nobody has solved this before – it’s probably really hard”. We can also add some additional assumptions -
In a photograph of a sudoku puzzle, the puzzle is going to be the main/most important object on the page A user is going to be photographing the puzzle – they aren’t going to take a picture of a whole newspaper page, they won’t be taking a photograph of a coffee shop and expecting us to find a sudoku puzzle that someone is playing four tables away. Also, the user is going to try and capture the whole puzzle, they won’t miss a corner or chop off the top.
The puzzle will be orientated reasonably correctly. No-one (hopefully) is going to be taking a picture of an upside down puzzle, and typically they will be trying to align it nicely in the camera viewfinder so it is reasonably straight without too much distortion.
A great example of how some simple assumptions made about your problem make it far easier to solve. Of course, the key is making sure the assumptions are valid, or being prepared to handle edge cases where these assumptions prove false.