Title

Poster Session A: Fingerprint Matching using Ridge Patterns

Abstract/Description

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.

Location

Crystal Ball Room A, Hotel Pearl Continental, Karachi, Pakistan

Session Theme

Poster Session A: Artificial Intelligence [AI-1]

Session Type

Poster Session

Session Chair

Dr. Arshad B. Siddiqui

Start Date

28-8-2005 12:05 PM

End Date

28-8-2005 12:25 PM

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Aug 28th, 12:05 PM Aug 28th, 12:25 PM

Poster Session A: Fingerprint Matching using Ridge Patterns

Crystal Ball Room A, Hotel Pearl Continental, Karachi, Pakistan

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.