A fingerprint is characterized by a pattern of interleaved ridges (dark lines) and valleys(bright lines). Generally, ridges and valleys run in parallel and sometimes they terminate or they bifurcate. At a global level, the fingerprint may present regions with patterns of high curvature, these regions are also called singularity. At the local level, other important feature called minutia can be found in the fingerprint patterns. Minutia mean small details, and this refers to the behavior of the ridges discontinuities such as termination, bifurcation and trifurcation or other features such as pores (small holes inside the ridges), lake (two closed bifurcations), dot (short ridges), etc. Most system uses only the termination and bifurcations. With the objective of matching the fingerprints we need to extract the fingerprint features such as minutiae and singularity points. From the fingerprint we can also extract other global information such as orientation and frequency of the ridge regions.
In this section we will see how to extract the local feature such as minutiae and global feature such as singularity. Both information are very important for a reliable matching. We will see also other features such as orientation map which will be used directly for the minutia and singularity extraction.