Minutia verification and classification for fingerprint matching
We propose a feedback path for the feature extraction stage, followed by a feature refinement stage for improving the matching performance. This performance improvement is illustrated in the context of a minutia-based fingerprint verification system. We show that a minutia verification stage based on re-examining the gray-scale profile in a detected minutia's spatial neighborhood in the sensed image can improve the matching performance by /spl sim/4% on our database. Further, we show that a feature refinement stage which assigns a class label to each detected minutia (ridge ending and ridge bifurcation) before matching can also improve the matching performance by /spl sim/3%. A combination of feedback (minutia verification) in the feature extraction phase and feature refinement (minutia classification) improves the overall performance of the fingerprint verification system by /spl sim/8%.