Fingerprint Matching using Ridge Patterns

This paper presents a fingerprint matching scheme that utilizes a ridge patterns to match fingerprint images. The proposed scheme uses a set of 16 Gabor filters where spatial frequencies correspond to the average inter-ridge spacing in fingerprints. It is used to capture the ridge strength at equally spaced orientations. A circular tessellation of filtered image is then used to construct the ridge feature map. This ridge feature map contains both global and local details in a fingerprint as a compact fixed length feature vector. The fingerprint matching is based on the Euclidean distance between two corresponding feature vectors. The genuine accept rate of the Ridge Pattern based matcher is observed to be about 5% to 8% higher than that of minutiae-based matcher at low false accept rates. Fingerprint feature extraction and matching takes nearly 7 seconds on a normal Pentium IV machine.