Real-time minutiae extraction in fingerprint images

Feature extraction is one of the most important tasks in an automatic fingerprint identification system (AFIS). The characteristics to be extracted in a given fingerprint image can be divided into two main categories: global or high-level features and local or low-level features. Cores and deltas are examples of global features. Their number and location in the fingerprint are used to classify the fingerprint (given a previously defined set of possible classes). Local features (such as endings and/or bifurcations of fingerprint ridges) are used to obtain a unique characterization of the given fingerprint. These local features are commonly named minutiae. The paper begins with a broad description of a proposed method for minutiae extraction. The different modules of the system are subsequently explained. Some examples of the application of the method on real fingerprint images taken from two different databases are discussed.