{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T04:50:07Z","timestamp":1747198207981,"version":"3.40.5"},"reference-count":42,"publisher":"Walter de Gruyter GmbH","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,11,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Biometric authentication received considerable attention lately. The vein pattern on the back of the hand is a unique biometric that can be measured through thermal imaging. Detecting this pattern provides an implicit approach that can authenticate users while interacting. In this paper, we present the Vein-Identification system, called VPID. It consists of a vein pattern recognition pipeline and an authentication part. We implemented six different vein-based authentication approaches by combining thermal imaging and computer vision algorithms. Through a study, we show that the approaches achieve a low false-acceptance rate (\u201cFAR\u201d) and a low false-rejection rate (\u201cFRR\u201d). Our findings show that the best approach is the Hausdorff distance-difference applied in combination with a Convolutional Neural Networks (CNN) classification of stacked images.<\/jats:p>","DOI":"10.1515\/icom-2019-0009","type":"journal-article","created":{"date-parts":[[2020,1,14]],"date-time":"2020-01-14T09:01:57Z","timestamp":1578992517000},"page":"259-270","source":"Crossref","is-referenced-by-count":6,"title":["VPID: Towards Vein Pattern Identification Using Thermal Imaging"],"prefix":"10.1515","volume":"18","author":[{"given":"Sarah","family":"Faltaous","sequence":"first","affiliation":[{"name":"27170 University of Duisburg-Essen , Essen , Germany"}]},{"given":"Jonathan","family":"Liebers","sequence":"additional","affiliation":[{"name":"27170 University of Duisburg-Essen , Essen , Germany"}]},{"given":"Yomna","family":"Abdelrahman","sequence":"additional","affiliation":[{"name":"240143 Bundeswehr University Munich , Munchen , Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8354-2195","authenticated-orcid":false,"given":"Florian","family":"Alt","sequence":"additional","affiliation":[{"name":"240143 Bundeswehr University Munich , Munchen , Germany"}]},{"given":"Stefan","family":"Schneegass","sequence":"additional","affiliation":[{"name":"27170 University of Duisburg-Essen , Essen , Germany"}]}],"member":"374","published-online":{"date-parts":[[2020,1,14]]},"reference":[{"key":"2023033119042587299_j_icom-2019-0009_ref_001","unstructured":"Vein recognition in Europe, Biometric Technology Today (2004)."},{"key":"2023033119042587299_j_icom-2019-0009_ref_002","doi-asserted-by":"crossref","unstructured":"Yomna Abdelrahman, Mohamed Khamis, Stefan Schneegass and Florian Alt, Stay cool! 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