The myth of goats :: how many people have fingerprints that are hard to match?

The proportion of people who have fingerprints that are particularly hard to match (also known as “Goats”) is a topic of great interest in biometrics, especially for those involved in the design, development, or evaluation of fingerprint-based identification or verification systems. There have been a variety of statements made in the recent past that a small percentage of people (usually 2%) cannot be fingerprinted due to poor quality fingers. This study shows these statements are based on misconceptions: the fact that some small percentage of fingerprints may be hard to match does not mean that a corresponding percentage of people are hard to match. This study describes the results of tests using fingerprint data collected operationally by US-VISIT. Ten sets of right and left index fingerprints from each of 6,000 individuals were used in the evaluation. Two of the more accurate matchers from the NIST Software Development Kit (SDK) tests were used. The definition of a Goat, or person whose fingerprints are intrinsically hard to match, varies. However, results clearly show that the proportion of Goats is very small, regardless of the definition. None of the 6,000 subjects had fingers that were always hard to match (with single-finger mate scores worse than a threshold corresponding to a verification False Accept Rate of 1%); less than 0.05% of the subjects had fingers that were usually hard to match; less than 0.3% of the subjects had fingers that were hard to match even a quarter of the time. Many individuals were particularly easy to match: for 77% to 81% of subjects, every fingerprint comparison had mate scores better than a threshold corresponding to a verification False Accept Rate of 10-6 (0.0001%). This study concludes that for the subject population (frequent users of US-VISIT) fingerprints that are hard to match cannot generally be attributed to intrinsic characteristics of a person’s fingerprints, but should be attributed to collection problems or other characteristics of the specific fingerprints used. Note that these results should be generalized with caution: results obtained using less accurate matchers, data from a source with lower operational quality controls, or substantively different subject populations would be likely to differ.