Nonlinear phase portrait modeling of fingerprint orientation

Fingerprint orientation is crucial for automatic fingerprint identification. However, recovery of orientation is still difficult especially in noisy region. A way to aid recovery of the orientation is to provide an orientation model. In this paper, an orientation model for the entire fingerprint orientation using high order phase portrait is suggested. Proper analysis of the orientation pattern at the singular point regions is provided. Then a low-order phase portrait near each of the singular point is added as constraint to the high-order phase portrait to provide accurate orientation modeling for the entire fingerprint image. The main advantage of the proposed approach is that the nonlinear model itself is able to model all type of fingerprint orientations completely. Experiments and visual analysis show the effectiveness of the proposed model.