{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T00:46:14Z","timestamp":1770338774052,"version":"3.49.0"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Circuits Syst Signal Process"],"published-print":{"date-parts":[[2022,11]]},"DOI":"10.1007\/s00034-022-02089-1","type":"journal-article","created":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T17:08:59Z","timestamp":1656695339000},"page":"6354-6369","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["HQ-finGAN: High-Quality Synthetic Fingerprint Generation Using GANs"],"prefix":"10.1007","volume":"41","author":[{"given":"Ataher","family":"Sams","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Homaira Huda","family":"Shomee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1885-1658","authenticated-orcid":false,"given":"S. M. Mahbubur","family":"Rahman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,1]]},"reference":[{"key":"2089_CR1","doi-asserted-by":"crossref","unstructured":"M.M. Ali, V.H. Mahale, P. Yannawar, A. Gaikwad, Overview of fingerprint recognition system, in: Proceedings of the International Conference on Electrical, Electronics, and Optimization Techniques, Chennai, India, pp. 1334\u20131338 (2016). https:\/\/doi.org\/10.1109\/ICEEOT.2016.7754900","DOI":"10.1109\/ICEEOT.2016.7754900"},{"key":"2089_CR2","unstructured":"A.H. Ansari, Generation and storage of large synthetic fingerprint database. ME Thesis, (2011) https:\/\/dsl.cds.iisc.ac.in\/thesis\/afzal.pdf"},{"key":"2089_CR3","doi-asserted-by":"crossref","unstructured":"M. Attia, M.H. Attia, J. Iskander, K. Saleh, D. Nahavandi, A. Abobakr, M. Hossny, S. Nahavandi, Fingerprint synthesis via latent space representation, in: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Bari, Italy, pp. 1855\u20131861 (2019). https:\/\/doi.org\/10.1109\/SMC.2019.8914499","DOI":"10.1109\/SMC.2019.8914499"},{"key":"2089_CR4","doi-asserted-by":"crossref","unstructured":"P. Bontrager, A. Roy, J. Togelius, N. Memon, A. Ross, Deepmasterprints: generating masterprints for dictionary attacks via latent variable evolution, in: Proceedings of the IEEE International Conference on Biometrics Theory, Applications and Systems, California, USA, pp.\u00a01\u20139 (2018). https:\/\/doi.org\/10.1109\/BTAS.2018.8698539","DOI":"10.1109\/BTAS.2018.8698539"},{"key":"2089_CR5","doi-asserted-by":"crossref","unstructured":"K. Cao, A. Jain, Fingerprint synthesis: evaluating fingerprint search at scale, in: Proceedings of the IEEE International Conference on Biometrics, Gold Coast, QLD, Australia, pp.\u00a031\u201338 (2018). https:\/\/doi.org\/10.1109\/ICB2018.2018.00016","DOI":"10.1109\/ICB2018.2018.00016"},{"key":"2089_CR6","doi-asserted-by":"crossref","unstructured":"R. Cappelli, D. Maio, D. Maltoni, Synthetic fingerprint-database generation, in: Proceedings of the International Conference on Pattern Recognition, Quebec City, Canada, vol. 3, pp. 744\u2013747 (2002). https:\/\/doi.org\/10.1109\/ICPR.2002.1048096","DOI":"10.1109\/ICPR.2002.1048096"},{"issue":"10","key":"2089_CR7","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0111099","volume":"9","author":"S Chen","year":"2014","unstructured":"S. Chen, S. Chang, Q. Huang, J. He, H. Wang, Q. Huang, Svm-based synthetic fingerprint discrimination algorithm and quantitative optimization strategy. PLoS ONE 9(10), e111,099 (2014). https:\/\/doi.org\/10.1371\/journal.pone.0111099","journal-title":"PLoS ONE"},{"key":"2089_CR8","doi-asserted-by":"crossref","unstructured":"V. Evdokimova, M. Petrov, M. Klyueva, N. Firsov, S. Bibikov, R. Skidanov, S. Popov, A. Nikonorov, Study of gan-based image reconstruction for diffractive optical systems, in: Proceedings of the International Conference on Information Technology and Nanotechnology, pp.\u00a01\u20134 (2020). https:\/\/doi.org\/10.1109\/ITNT49337.2020.9253168","DOI":"10.1109\/ITNT49337.2020.9253168"},{"key":"2089_CR9","doi-asserted-by":"publisher","first-page":"92918","DOI":"10.1109\/ACCESS.2020.2994371","volume":"8","author":"MA Fahim","year":"2020","unstructured":"M.A. Fahim, H.Y. Jung, A lightweight GAN network for large scale fingerprint generation. IEEE Access 8, 92918\u201392928 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.2994371","journal-title":"IEEE Access"},{"issue":"4","key":"2089_CR10","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1049\/iet-bmt.2013.0065","volume":"3","author":"C Gottschlich","year":"2014","unstructured":"C. Gottschlich, S. Huckemann, Separating the real from the synthetic: minutiae histograms as fingerprints of fingerprints. IET Biom. 3(4), 291\u2013301 (2014)","journal-title":"IET Biom."},{"issue":"8","key":"2089_CR11","doi-asserted-by":"publisher","first-page":"777","DOI":"10.1109\/34.709565","volume":"20","author":"L Hong","year":"1998","unstructured":"L. Hong, Y. Wan, A. Jain, Fingerprint image enhancement: algorithm and performance evaluation. IEEE Trans. Pattern Anal. Mach. Intell. 20(8), 777\u2013789 (1998). https:\/\/doi.org\/10.1109\/34.709565","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2089_CR12","doi-asserted-by":"crossref","unstructured":"P. Isola, J.Y. Zhu, T. Zhou, A.A. Efros, Image-to-image translation with conditional adversarial networks, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, Hawaii, USA, pp. 1125\u20131134 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.632","DOI":"10.1109\/CVPR.2017.632"},{"issue":"2","key":"2089_CR13","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1109\/TIFS.2006.873653","volume":"1","author":"AK Jain","year":"2006","unstructured":"A.K. Jain, A. Ross, S. Pankanti, Biometrics: a tool for information security. IEEE Trans. Inf. Forensics Secur. 1(2), 125\u2013143 (2006). https:\/\/doi.org\/10.1109\/TIFS.2006.873653","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"2089_CR14","doi-asserted-by":"crossref","unstructured":"T. Karras, S. Laine, T. Aila, A style-based generator architecture for generative adversarial networks, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA, pp. 4401\u20134410 (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.00453","DOI":"10.1109\/CVPR.2019.00453"},{"key":"2089_CR15","doi-asserted-by":"crossref","unstructured":"T. Karras, S. Laine, M. Aittala J., Hellsten, J. Lehtinen, T. Aila, Analyzing and improving the image quality of stylegan, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Seattle, USA, pp. 8110\u20138119 (2020). https:\/\/doi.org\/10.1109\/CVPR42600.2020.00813","DOI":"10.1109\/CVPR42600.2020.00813"},{"key":"2089_CR16","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.isprsjprs.2021.07.007","volume":"179","author":"X Li","year":"2021","unstructured":"X. Li, Z. Du, Y. Huang, Z. Tan, A deep translation (GAN) based change detection network for optical and sar remote sensing images. J. Photogramm. Remote Sens. 179, 14\u201334 (2021). https:\/\/doi.org\/10.1016\/j.isprsjprs.2021.07.007","journal-title":"J. Photogramm. Remote Sens."},{"issue":"4","key":"2089_CR17","doi-asserted-by":"publisher","first-page":"2008","DOI":"10.1109\/TIP.2017.2788866","volume":"27","author":"C Lin","year":"2018","unstructured":"C. Lin, A. Kumar, Matching contactless and contact-based conventional fingerprint images for biometrics identification. IEEE Trans. Image Process. 27(4), 2008\u20132021 (2018). https:\/\/doi.org\/10.1109\/TIP.2017.2788866","journal-title":"IEEE Trans. Image Process."},{"key":"2089_CR18","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-84882-254-2","volume-title":"Handbook of Fingerprint Recognition","author":"D Maltoni","year":"2009","unstructured":"D. Maltoni, D. Maio, A.K. Jain, S. Prabhakar, Handbook of Fingerprint Recognition (Springer, Berlin, 2009)"},{"key":"2089_CR19","unstructured":"S. Minaee, A. Abdolrashidi, Finger-GAN: generating realistic fingerprint images using connectivity imposed gan (2018). arXiv preprint arXiv:1812.10482"},{"key":"2089_CR20","unstructured":"Neurotechnology, VeriFinger SDK, VeriFinger fingerprint recognition technology, algorithm and SDK for PC, smartphones and Web (2022) https:\/\/www.neurotechnology.com\/verifinger.html Accessed June 10, (2022)"},{"key":"2089_CR21","unstructured":"Novetta Biosynthetic Software (2014) https:\/\/www.novetta.com\/wp-content\/uploads\/2014\/11\/NOVBiosyntheticsOverview2.pdf"},{"key":"2089_CR22","unstructured":"E. Tabassi, Nfiq 2.0: Nist fingerprint image quality. NISTIR 8034 (2016)"},{"key":"2089_CR23","doi-asserted-by":"publisher","unstructured":"The Forensic Use of Bioinformation: Ethical Issues Jahrbuch f\u00fcr Wissenschaft und Ethik 13(1):419\u2013430. (2008) https:\/\/doi.org\/10.1515\/9783110196832.3.419","DOI":"10.1515\/9783110196832.3.419"},{"key":"2089_CR24","doi-asserted-by":"crossref","unstructured":"Z. Wang, E.P. Simoncelli, A.C. Bovik, Multiscale structural similarity for image quality assessment, in: Proceedings of the Thirty-Seventh Asilomar Conference on Signals, Systems & Computers, Pacific Grove, CA, USA, pp. 1398\u20131402 (2003). https:\/\/doi.org\/10.1109\/ACSSC.2003.1292216","DOI":"10.1109\/ACSSC.2003.1292216"},{"key":"2089_CR25","doi-asserted-by":"crossref","unstructured":"A.V. Wyzykowski, M. Segundo, R. de\u00a0Paula\u00a0Lemes, Level three synthetic fingerprint generation, in: Proceedings of the International Conference on Pattern Recognition, Milan, Italy, pp. 9250\u20139257 (2021). https:\/\/doi.org\/10.1109\/ICPR48806.2021.9412304","DOI":"10.1109\/ICPR48806.2021.9412304"},{"key":"2089_CR26","doi-asserted-by":"crossref","unstructured":"Q. Zhao, L. Zhang, D. Zhang, N. Luo, Direct pore matching for fingerprint recognition, in: Proceedings of the International conference on Biometrics, Alghero, Italy, pp. 597\u2013606 (2009). https:\/\/doi.org\/10.1007\/978-3-642-01793-3_61","DOI":"10.1007\/978-3-642-01793-3_61"},{"key":"2089_CR27","doi-asserted-by":"crossref","unstructured":"Q. Zhao, A.K. Jain, N.G. Paulter, M. Taylor, Fingerprint image synthesis based on statistical feature models, in: Proceedings of the IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems, Arlington, Virginia, USA, pp.\u00a023\u201330 (2012). https:\/\/doi.org\/10.1109\/BTAS.2012.6374554","DOI":"10.1109\/BTAS.2012.6374554"},{"key":"2089_CR28","doi-asserted-by":"crossref","unstructured":"J.Y. Zhu, T. Park, P. Isola, A.A. Efros, Unpaired image-to-image translation using cycle-consistent adversarial networks, in: Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy, pp. 2223\u20132232 (2017). https:\/\/doi.org\/10.1109\/ICCV.2017.244","DOI":"10.1109\/ICCV.2017.244"}],"container-title":["Circuits, Systems, and Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00034-022-02089-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00034-022-02089-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00034-022-02089-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T16:55:09Z","timestamp":1664988909000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00034-022-02089-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,1]]},"references-count":28,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2022,11]]}},"alternative-id":["2089"],"URL":"https:\/\/doi.org\/10.1007\/s00034-022-02089-1","relation":{},"ISSN":["0278-081X","1531-5878"],"issn-type":[{"value":"0278-081X","type":"print"},{"value":"1531-5878","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,1]]},"assertion":[{"value":"21 September 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 June 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 June 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 July 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval"}},{"value":"Consent was obtained from all individual participants included in the human perception test.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to Participate"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for Publication"}}]}}