Probabilistic Orientation Field Estimation for Fingerprint Enhancement and Verification

The authors present a novel probabilistic method to estimate the orientation field in fingerprint images. Traditional approach based on the smoothing of local image gradients usually generates unsatisfactory results in poor quality regions of fingerprint images. They show how to improve the orientation field estimation by first constructing a Markov Random Field (MRF) and then inferring the orientation field from the MRF model. The MRF is made up of two components.