{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:33:01Z","timestamp":1760243581021,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2013,9,4]],"date-time":"2013-09-04T00:00:00Z","timestamp":1378252800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Conventional fingerprint verification systems use only static information. In this paper, fingerprint videos, which contain dynamic information, are utilized for verification. Fingerprint videos are acquired by the same capture device that acquires conventional fingerprint images, and the user experience of providing a fingerprint video is the same as that of providing a single impression. After preprocessing and aligning processes, \u201cinside similarity\u201d and \u201coutside similarity\u201d are defined and calculated to take advantage of both dynamic and static information contained in fingerprint videos. Match scores between two matching fingerprint videos are then calculated by combining the two kinds of similarity. Experimental results show that the proposed video-based method leads to a relative reduction of 60 percent in the equal error rate (EER) in comparison to the conventional single impression-based method. We also analyze the time complexity of our method when different combinations of strategies are used. Our method still outperforms the conventional method, even if both methods have the same time complexity. Finally, experimental results demonstrate that the proposed video-based method can lead to better accuracy than the multiple impressions fusion method, and the proposed method has a much lower false acceptance rate (FAR) when the false rejection rate (FRR) is quite low.<\/jats:p>","DOI":"10.3390\/s130911660","type":"journal-article","created":{"date-parts":[[2013,9,4]],"date-time":"2013-09-04T12:31:59Z","timestamp":1378297919000},"page":"11660-11686","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Video-Based Fingerprint Verification"],"prefix":"10.3390","volume":"13","author":[{"given":"Wei","family":"Qin","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Shandong University, Jinan 250101, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yilong","family":"Yin","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Shandong University, Jinan 250101, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lili","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Shandong University, Jinan 250101, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2013,9,4]]},"reference":[{"key":"ref_1","unstructured":"Lee, H.C., and Gaensslen, R.E. 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