Fingerprint-based identification can be placed into two categories: Minutae-based matching (analysing the local structure) and global pattern matching (analysing the global structure). Currently the computer aided fingerprint recognition is using the minutiae-based matching. Minutiae points are local ridge characteristics that appear as either a ridge ending or a ridge bifurcation.

The uniqueness of a fingerprint can be determined by the pattern of the ridges and the valleys a fingerprint is made of. A complete fingerprint consists of about 100 minutiae points in average. The measured fingerprint-area consists in average of about 30-60 minutiae points depending on the finger and on the sensor area.

These minutiae points are represented by a cloud of dots in a coordinate system. They are stored together with the angle of the tangent of a local minutiae point in a fingerprint-code or directly in a reference template. A template can consist of more than one fingerprint-code to expand the amount of information and to expand the enrolled fingerprint area. In general this leads to a higher template quality and therefore to a higher similarity value of the template and the sample.

The template sizes varies from 100 bytes to 1500 Bytes depending on the algorithm and the quality of a fingerprint. Nevertheless, very rarely there are fingerprints without any minutiae-points that leads to a failure to enroll (FER = Failure to Enroll Rate). It is also difficult to extract the minutiae points accurately when the fingerprint has got a low quality.