{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:01:58Z","timestamp":1760144518449,"version":"build-2065373602"},"reference-count":84,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T00:00:00Z","timestamp":1714348800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Biometric fingerprint identification hinges on the reliability of its sensors; however, calibrating and standardizing these sensors poses significant challenges, particularly in regards to repeatability and data diversity. To tackle these issues, we propose methodologies for fabricating synthetic 3D fingerprint targets, or phantoms, that closely emulate real human fingerprints. These phantoms enable the precise evaluation and validation of fingerprint sensors under controlled and repeatable conditions. Our research employs laser engraving, 3D printing, and CNC machining techniques, utilizing different materials. We assess the phantoms\u2019 fidelity to synthetic fingerprint patterns, intra-class variability, and interoperability across different manufacturing methods. The findings demonstrate that a combination of laser engraving or CNC machining with silicone casting produces finger-like phantoms with high accuracy and consistency for rolled fingerprint recordings. For slap recordings, direct laser engraving of flat silicone targets excels, and in the contactless fingerprint sensor setting, 3D printing and silicone filling provide the most favorable attributes. Our work enables a comprehensive, method-independent comparison of various fabrication methodologies, offering a unique perspective on the strengths and weaknesses of each approach. This facilitates a broader understanding of fingerprint recognition system validation and performance assessment.<\/jats:p>","DOI":"10.3390\/s24092847","type":"journal-article","created":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T04:01:52Z","timestamp":1714449712000},"page":"2847","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Toward Synthetic Physical Fingerprint Targets"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0823-9601","authenticated-orcid":false,"given":"Laurenz","family":"Ruzicka","sequence":"first","affiliation":[{"name":"Austrian Institute of Technology, 1210 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8920-0468","authenticated-orcid":false,"given":"Bernhard","family":"Strobl","sequence":"additional","affiliation":[{"name":"Austrian Institute of Technology, 1210 Vienna, Austria"}]},{"given":"Stephan","family":"Bergmann","sequence":"additional","affiliation":[{"name":"Bundesamt f\u00fcr Sicherheit in der Informationstechnik, 53175 Bonn, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-1619-2637","authenticated-orcid":false,"given":"Gerd","family":"Nolden","sequence":"additional","affiliation":[{"name":"Bundesamt f\u00fcr Sicherheit in der Informationstechnik, 53175 Bonn, Germany"}]},{"given":"Tom","family":"Michalsky","sequence":"additional","affiliation":[{"name":"IDloop GmbH, 07745 Jena, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7831-3082","authenticated-orcid":false,"given":"Christoph","family":"Domscheit","sequence":"additional","affiliation":[{"name":"IDloop GmbH, 07745 Jena, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0985-7735","authenticated-orcid":false,"given":"Jannis","family":"Priesnitz","sequence":"additional","affiliation":[{"name":"Hochschule Darmstadt, 64295 Darmstadt, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8753-4346","authenticated-orcid":false,"given":"Florian","family":"Bl\u00fcmel","sequence":"additional","affiliation":[{"name":"Biometrie-Evaluations-Zentrum (BEZ) Hochschule Bonn-Rhein-Sieg, 53757 Sankt Augustin, Germany"}]},{"given":"Bernhard","family":"Kohn","sequence":"additional","affiliation":[{"name":"Austrian Institute of Technology, 1210 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1613-5164","authenticated-orcid":false,"given":"Clemens","family":"Heitzinger","sequence":"additional","affiliation":[{"name":"Institute of Information Systems Engineering\/Research Unit of Machine Learning, Technische Universit\u00e4t Wien, 1040 Vienna, Austria"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.forsciint.2019.01.046","article-title":"The permanence of friction ridge skin and persistence of friction ridge skin and impressions: A comprehensive review and new results","volume":"297","author":"Monson","year":"2019","journal-title":"Forensic Sci. 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