1. A method for matching distorted fingerprints, the method implemented by an automatic fingerprint identification system including a processor, a memory coupled to the processor, an interface to a fingerprint scanning device, and a sensor associated with the fingerprint scanning device that indicates a fingerprint match, the method comprising: selecting (i) a list of search minutia extracted from a search fingerprint, and (ii) a list of reference minutia extracted from a reference fingerprint; for each particular search minutia included in the list of search minutiae, identifying a corresponding reference minutia from the list of reference minutiae that is a closest matched minutia to the particular search minutia; generating a first list of locally matched minutiae between the search fingerprint and the reference fingerprint that includes each of the particular search minutiae, and each corresponding reference minutia that is the closest matched minutia to each of the particular search minutiae; identifying a first set of globally aligned minutiae pairs from among the first list of locally matched minutiae pairs based at least on performing a global alignment procedure on a first subset of the first list of locally matched minutiae pairs; computing (i) a first similarity score between the list of particular search minutiae and the list of corresponding reference minutiae within the first set of globally aligned minutiae pairs, and (ii) a center coordinate for the first set of globally aligned minutiae pairs; generating a second list of locally matched minutiae pairs, based at least on removing each of the particular search minutiae and each corresponding reference minutia that is the closest matched minutia to each of the particular search minutiae, that are included in the first set of globally aligned minutiae pairs, from the first list of locally matched minutiae pairs; identifying a second set of globally aligned minutiae pairs from among the second list of locally matched minutiae pairs based at least on performing the global alignment procedure on a second subset of the second list of locally matched minutiae pairs; determining that a number of globally aligned minutiae pairs within the second set of globally aligned minutiae pairs exceeds a threshold value; computing (i) a second similarity score between the list of particular search minutiae and the list of corresponding reference minutiae within the second set of globally aligned minutiae pairs, and (ii) a center coordinate for the second set of globally aligned minutiae pairs; identifying one or more additional sets of globally aligned minutiae pairs from among the second list of locally matched minutiae pairs based at least on successively performing the global alignment procedure on one or more additional subsets of the second list of locally matched minutiae pairs until the second list of locally matched minutiae pairs does not contain any particular search minutia, wherein: each successive individual subset from the one or more additional subsets of the second list of locally matched minutia pairs includes particular search minutiae and the corresponding reference minutiae that are not included in a prior individual subset that was previously identified based at least on performing a prior global alignment procedure, and after performing the global alignment procedure on each successive individual subset, removing each of the particular search minutiae and each of the corresponding reference minutiae that are included in the prior individual subset from the second list of locally matched minutiae pairs; computing (i) additional similarity scores between the list of particular search minutiae and the list of corresponding reference minutiae within each of the one or more additional sets of globally aligned minutiae pairs of globally aligned minutiae pairs, and (ii) a center coordinate for each of the one or more additional sets of globally aligned minutiae pairs of globally aligned minutiae pairs; determining a geometric consistency metric between (i) the center coordinate for the first set of globally aligned minutiae pairs, (ii) the center coordinate for the second set of globally aligned minutiae pairs, and (iii) the center coordinates for each of the one or more additional sets of globally aligned minutiae pairs; computing a final similarity score based at least on (i) combining the first similarity score, the second similarity score, and the additional similarity scores, and (ii) the geometric consistency metric; and providing, for output to the automatic fingerprint identification system, the final similarity score for use in a particular fingerprint matching operation between the search fingerprint and the reference fingerprint.