Fingerprint verification thumb|160px|Ridge ending thumb|160px|Bifurcation thumb|160px|Short ridge (dot) Fingerprints can be captured as graphical ridge and valley patterns. Because of their uniqueness and permanence, fingerprints emerged as the most widely used biometric identifier in the 2000s. Automated fingerprint verification systems were developed to meet the needs of law enforcement and their use became more widespread in civilian applications. Despite being deployed more widely, reliable automated fingerprint verification remained a challenge and was extensively researched in the context of pattern recognition and image processing. The uniqueness of a fingerprint can be established by the overall pattern of ridges and valleys, or the logical ridge discontinuities known as minutiae. In the 2000s, minutiae features were considered the most discriminating and reliable feature of a fingerprint. Therefore, the recognition of minutiae features became the most common basis for automated fingerprint verification. The most widely used minutiae features used for automated fingerprint verification were the ridge ending and the ridge bifurcation.
fingerprint verification thumb|160px|ridge ending thumb|160px|bifurcation thumb|160px|short ridge (dot) fingerprints can be captured as graphical ridge and valley patterns because of their uniqueness and permanence fingerprints emerged as the most widely used biometric identifier in the 2000s automated fingerprint verification systems were developed to meet the needs of law enforcement and their use became more widespread in civilian applications despite being deployed more widely reliable automated fingerprint verification remained a challenge and was extensively researched in the context of pattern recognition and image processing the uniqueness of a fingerprint can be established by the overall pattern of ridges and valleys or the logical ridge discontinuities known as minutiae in the 2000s minutiae features were considered the most discriminating and reliable feature of a fingerprint therefore the recognition of minutiae features became the most common basis for automated fingerprint verification the most widely used minutiae features used for automated fingerprint verification were the ridge ending and the ridge bifurcation