Fingerprint recognition with ridge features and minutiae on distortion

Abstract

In this paper we present a new fingerprint matching method which combines different features, including minutiae and ridge features. The ridge features contain ridge count, ridge length, ridge curvature direction and ridge frequency. All ridge features are extracted in blocks around each minutia. The similarity scores of the features are summed with different weighting values as the final score of two fingerprints. Experiments are conducted on the FVC2002 database to compare the proposed method with other fingerprint methods on equal error rate (EER). The proposed method achieves better performance than other methods. The average EER value of the proposed method is 0.82 whereas the average EER value of the conventional matching method is 8.12.