Lee, Wonjune Cho, Sungchul Choi, Heeseung Kim, Jaihie 2024-01-20T00:03:51Z 2024-01-20T00:03:51Z 2022-01-25 2017-11 0957-4174 https://pubs.kist.re.kr/handle/201004/122092 Currently, most mobile devices adopt very small fingerprint sensors that only capture small partial fingerprint images. Accordingly, conventional minutiae-based fingerprint matchers are not capable of providing convincing results due to the insufficiency of minutiae. To secure diverse mobile applications such as those requiring privacy protection and mobile payments, a more accurate fingerprint matcher is demanded. This manuscript proposes a new partial fingerprint-matching method incorporating new ridge shape features (RSFs) in addition to the conventional minutia features. These new RSFs represent the small ridge segments where specific edge shapes (concave and convex) are observed, and they are detectable in conventional 500 dpi images. The RSFs are effectively utilized in the proposed matching scheme which consists of minutiae matching and ridge-feature-matching stages. In the minutiae matching stage, corresponding minutia pairs are determined by comparing the local RSFs and minutiae adjacent to each minutia. During the subsequent ridge-feature-matching stage, the RSFs in the overlapped area of two images are further compared to enhance the matching accuracy. A final matching score is obtained by combining the resulting scores from the two matching stages. Various tests for partial matching were conducted on the FVC2002, FVC2004 and BERC (self-constructed) databases, and the proposed method shows significantly lower equal-error rates compared to other matching methods. The results show that the proposed method improves the accuracy of fingerprint recognition, especially for implementation in mobile devices where small fingerprint scanners are adopted. (C) 2017 Elsevier Ltd. All rights reserved. English Pergamon Press Ltd. Partial fingerprint matching using minutiae and ridge shape features for small fingerprint scanners Article 10.1016/j.eswa.2017.06.019 1 Expert Systems with Applications, v.87, pp.183 - 198 Expert Systems with Applications 87 183 198 N scie scopus 000407183900015 2-s2.0-85021051690 Computer Science, Artificial Intelligence Engineering, Electrical & Electronic Operations Research & Management Science Computer Science Engineering Operations Research & Management Science Article VERIFICATION ALGORITHM DESCRIPTORS Minutiae Partial fingerprint Ridge shape feature (RSF) Small fingerprint scanner