Fusion Method of Fingerprint Quality Evaluation: From the Local Gabor Feature to the Global Spatial-Frequency Structures

摘要

We propose a new fusion method to evaluate fingerprint quality by combining both spatial and frequency features of a fingerprint image. In frequency domain, a ring structure of DFT magnitude and directional Gabor features are applied. In spatial domain, black pixel ratio of central area is taken into account. These three features are the most efficient indexes for fingerprint quality assessment. Though additional features could be introduced, their slight improvement in performance will be traded off with complexity and computational load to some extent. Thus in this paper, each of the three features are first employed to assess fingerprint quality, their evaluation performance are also discussed. Then the suggested fusion approach of the three features is presented to obtain the final quality scores. We test the fusion method in our public security fingerprint database. Experimental results demonstrate that the proposed scheme can estimate the quality of fingerprint images accurately. It provides a feasible rejection of poor fingerprint images before they are presented to the fingerprint recognition system for feature extraction and matching.