I don't think there's a good solution to this problem without incorporating some kind of prior distribution, and a statistical model of what paws tend to look like. Heuristics will only take you so far.
edit: come to think of it, something like mean-shift or ICP would probably do very well on this.
Yes mean shift would do it nicely, heck most clustering methods should give good results - but I think they will need a paw model of some sort (even if it's just a basic template) to get up to the 98%+ accuracy levels.
edit: come to think of it, something like mean-shift or ICP would probably do very well on this.