  In fingerprint-based systems, the size of databases increases considerably
with population growth. In developing countries, because of the difficulty in
using a central system when enlisting voters, it often happens that several
regional voter databases are created and then merged to form a central
database. A process is used to remove duplicates and ensure uniqueness by
voter. Until now, companies specializing in biometrics use several costly
computing servers with algorithms to perform large-scale deduplication based on
fingerprints. These algorithms take a considerable time because of their
complexity in O (n2), where n is the size of the database. This article
presents an algorithm that can perform this operation in O (2n), with just a
computer. It is based on the development of an index obtained using a 5 * 5
matrix performed on each fingerprint. This index makes it possible to build
clusters of O (1) in size in order to compare fingerprints. This approach has
been evaluated using close to 11 4000 fingerprints, and the results obtained
show that this approach allows a penetration rate of less than 1%, an almost O
(1) identification, and an O (n) deduplication. A base of 10 000 000
fingerprints can be deduplicated with a just computer in less than two hours,
contrary to several days and servers for the usual tools.
  Keywords: fingerprint, cluster, index, deduplication.
