7. Hybrid Fingerprint Matcher
Most fingerprint matching systems rely on the distribution of minutiae on the fingertip to represent and match fingerprints. While the ridge flow pattern is generally used for classifying fingerprints, it is seldom used for matching. This work describes a hybrid fingerprint matching scheme that uses both minutiae and ridge flow information to represent and match fingerprints. A set of 8 Gabor filters, whose spatial frequencies correspond to the average inter-ridge spacing in fingerprints, is used to capture the ridge strength at equally spaced orientations. A square tessellation of the filtered images is then used to construct an eight-dimensional feature map, called the ridge feature map. The ridge feature map along with the minutiae set of a fingerprint image is used for matching purposes.
The proposed technique has the following features:
(i) the entire image is taken into account in constructing the ridge feature map, and every tessellated cell is equally weighted;
(ii) minutiae matching is used to determine the affine transformation parameters relating the query and the template images for ridge feature map extraction;
(iii) filtering and ridge feature map extraction are implemented in the frequency domain thereby speeding up the matching process;
(iv) filtered query images are cached to greatly increase the one-to-many matching speed. The hybrid matcher performs better than a minutiae-based fingerprint matching system. The genuine accept rate of the hybrid matcher is observed to be ~10% higher than that of a minutiae-based system at low FAR values. Fingerprint verification (one-to-one matching) using the hybrid matcher on a Pentium III, 800 MHz system takes ~1.4 seconds, while fingerprint identification (one-to-many matching) involving 1,000 templates takes ~0.2 seconds per match.
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