Improving Latent Fingerprint Matching Performance by Orientation Field Estimation using Localized Dictionaries?

Dictionary based orientation field estimation approach has shown great performance for latent fingerprints. In this paper, we use prior knowledge of fingerprints structure to improve the latent fingerprints matching performance. Considering the fact that ridge orientations at different locations of fingerprints have different characteristics, we propose a localized dictionaries-based orientation field estimation algorithm, in which noisy orientation patch at a location output by a local estimation approach is replaced by real orientation patch in the local dictionary at the same location.Dictionary of reference orientation patches is constructed using a set of orientation fields, which is extracted from high quality fingerprints The precondition of applying localized dictionaries is that the pose of the latent fingerprint needs to be estimated. Experimental results on challenging latent fingerprint datasets show the proposed method outperforms previous ones markedly