A Mathematical Modeling Method for Fingerprint Ridge Segmentation and Normalization
Series of Automatic Fingerprint Identification Systems (AFIS) exist for human identification. One of the indices for evaluating the contributions of these systems is the degree to which they enforce security through proper identification and verification of individuals. This degree is generally determined by the quality of the fingerprint images and the efficiency of the algorithm. Ridge normalization and segmentation are parts of the important and successive stages of a raw fingerprint image enhancement. In this paper, existing mathematical models for fingerprint ridge normalization and segmentation were modified for increased speed and accuracy.