It all depends on a given implementation's choice of a threshold to use. Two objects will give a score which indicates similarity/dissimilarity and then some fu

It all depends on a given implementation's choice of a threshold to use. Two objects will give a score which indicates similarity/dissimilarity and then some further logic needs to say if that score is good enough for a match. Some NIST certifications for instance end up placing requirements with false-match-rates at 1/10,000 (e.g. one left index finger matching someone else's left index finger at that frequency when trying a lot of random pairs).