{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:16:29Z","timestamp":1740147389987,"version":"3.37.3"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"6-7","license":[{"start":{"date-parts":[[2024,6,6]],"date-time":"2024-06-06T00:00:00Z","timestamp":1717632000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,6,6]],"date-time":"2024-06-06T00:00:00Z","timestamp":1717632000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100003995","name":"Natural Science Foundation of Anhui Province","doi-asserted-by":"publisher","award":["2108085MF206"],"award-info":[{"award-number":["2108085MF206"]}],"id":[{"id":"10.13039\/501100003995","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976006"],"award-info":[{"award-number":["61976006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1007\/s11760-024-03249-3","type":"journal-article","created":{"date-parts":[[2024,6,6]],"date-time":"2024-06-06T10:03:15Z","timestamp":1717668195000},"page":"5491-5501","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Fingerprint image super-resolution based on multi-class deep dictionary learning and ridge prior"],"prefix":"10.1007","volume":"18","author":[{"given":"Yi","family":"Huang","sequence":"first","affiliation":[]},{"given":"Weixin","family":"Bian","sequence":"additional","affiliation":[]},{"given":"Deqin","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Biao","family":"Jie","sequence":"additional","affiliation":[]},{"given":"Luo","family":"Feng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,6,6]]},"reference":[{"key":"3249_CR1","doi-asserted-by":"crossref","unstructured":"Yoon, S., Feng, J., Jain, A. K.: On latent fingerprint enhancement. In: Biometric Technology for Human Identification VII, vol. 7667, pp. 60\u201369. SPIE (2010)","DOI":"10.1117\/12.851411"},{"key":"3249_CR2","doi-asserted-by":"publisher","DOI":"10.1201\/9781420048810","volume-title":"Quantitative-Qualitative Friction Ridge Analysis: An Introduction to Basic and Advanced Ridgeology","author":"DR Ashbaugh","year":"1999","unstructured":"Ashbaugh, D.R.: Quantitative-Qualitative Friction Ridge Analysis: An Introduction to Basic and Advanced Ridgeology. CRC Press (1999)"},{"issue":"10","key":"3249_CR3","doi-asserted-by":"publisher","first-page":"1521","DOI":"10.1109\/83.951537","volume":"10","author":"X Li","year":"2001","unstructured":"Li, X., Orchard, M.T.: New edge-directed interpolation. IEEE Trans. Image Process. 10(10), 1521\u20131527 (2001)","journal-title":"IEEE Trans. Image Process."},{"issue":"11","key":"3249_CR4","doi-asserted-by":"publisher","first-page":"4271","DOI":"10.1109\/TIP.2013.2271849","volume":"22","author":"Z Wei","year":"2013","unstructured":"Wei, Z., Ma, K.K.: Contrast-guided image interpolation. IEEE Trans. Image Process. 22(11), 4271\u20134285 (2013)","journal-title":"IEEE Trans. Image Process."},{"key":"3249_CR5","doi-asserted-by":"crossref","unstructured":"Zhang, K., Gool, L. V., Timofte, R.: Deep unfolding network for image super-resolution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3217\u20133226. (2020)","DOI":"10.1109\/CVPR42600.2020.00328"},{"key":"3249_CR6","doi-asserted-by":"crossref","unstructured":"Yang, J., Wright, J., Huang, T., et al.: Image super-resolution as sparse representation of raw image patches. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20138. IEEE (2008)","DOI":"10.1109\/CVPR.2008.4587647"},{"issue":"4","key":"3249_CR7","first-page":"4713","volume":"45","author":"C Saharia","year":"2022","unstructured":"Saharia, C., Ho, J., Chan, W., et al.: Image super-resolution via iterative refinement. IEEE Trans. Pattern Anal. Mach. Intell. 45(4), 4713\u20134726 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3249_CR8","doi-asserted-by":"crossref","unstructured":"Zhang, X., Zeng, H., Guo, S., et al.: Efficient long-range attention network for image super-resolution. In: European Conference on Computer Vision, pp. 649\u2013667. Springer Nature Switzerland, Cham (2022)","DOI":"10.1007\/978-3-031-19790-1_39"},{"key":"3249_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.earscirev.2022.104110","volume":"232","author":"P Wang","year":"2022","unstructured":"Wang, P., Bayram, B., Sertel, E.: A comprehensive review on deep learning based remote sensing image super-resolution methods. Earth Sci. Rev. 232, 104110 (2022)","journal-title":"Earth Sci. Rev."},{"issue":"8","key":"3249_CR10","doi-asserted-by":"publisher","first-page":"5981","DOI":"10.1007\/s10462-022-10147-y","volume":"55","author":"H Liu","year":"2022","unstructured":"Liu, H., Ruan, Z., Zhao, P., et al.: Video super-resolution based on deep learning: a comprehensive survey. Artif. Intell. Rev. 55(8), 5981\u20136035 (2022)","journal-title":"Artif. Intell. Rev."},{"issue":"13","key":"3249_CR11","doi-asserted-by":"publisher","first-page":"1588","DOI":"10.3390\/rs11131588","volume":"11","author":"T Lu","year":"2019","unstructured":"Lu, T., Wang, J., Zhang, Y., et al.: Satellite image super-resolution via multi-scale residual deep neural network. Remote Sens. 11(13), 1588 (2019)","journal-title":"Remote Sens."},{"key":"3249_CR12","doi-asserted-by":"publisher","first-page":"10096","DOI":"10.1109\/ACCESS.2016.2611583","volume":"4","author":"S Tariyal","year":"2016","unstructured":"Tariyal, S., Majumdar, A., Singh, R., et al.: Deep dictionary learning. IEEE Access 4, 10096\u201310109 (2016)","journal-title":"IEEE Access"},{"issue":"10","key":"3249_CR13","doi-asserted-by":"publisher","first-page":"4790","DOI":"10.1109\/TIP.2019.2914376","volume":"28","author":"S Mahdizadehaghdam","year":"2019","unstructured":"Mahdizadehaghdam, S., Panahi, A., Krim, H., et al.: Deep dictionary learning: a parametric network approach. IEEE Trans. Image Process. 28(10), 4790\u20134802 (2019)","journal-title":"IEEE Trans. Image Process."},{"key":"3249_CR14","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/j.patcog.2019.02.018","volume":"91","author":"J Song","year":"2019","unstructured":"Song, J., Xie, X., Shi, G., et al.: Multi-layer discriminative dictionary learning with locality constraint for image classification. Pattern Recogn. 91, 135\u2013146 (2019)","journal-title":"Pattern Recogn."},{"issue":"5","key":"3249_CR15","doi-asserted-by":"publisher","first-page":"2129","DOI":"10.1109\/TNNLS.2020.2997289","volume":"32","author":"H Tang","year":"2020","unstructured":"Tang, H., Liu, H., Xiao, W., et al.: When dictionary learning meets deep learning: deep dictionary learning and coding network for image recognition with limited data. IEEE Trans Neural Netw. Learn. Syst. 32(5), 2129\u20132141 (2020)","journal-title":"IEEE Trans Neural Netw. Learn. Syst."},{"key":"3249_CR16","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1007\/s00371-020-01970-x","volume":"37","author":"A Montazeri","year":"2021","unstructured":"Montazeri, A., Shamsi, M., Dianat, R.: MLK-SVD, the new approach in deep dictionary learning. Vis. Comput. 37, 707\u2013715 (2021)","journal-title":"Vis. Comput."},{"issue":"11","key":"3249_CR17","doi-asserted-by":"publisher","first-page":"4311","DOI":"10.1109\/TSP.2006.881199","volume":"54","author":"M Aharon","year":"2006","unstructured":"Aharon, M., Elad, M., Bruckstein, A.: K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation. IEEE Trans. Signal Process. 54(11), 4311\u20134322 (2006)","journal-title":"IEEE Trans. Signal Process."},{"key":"3249_CR18","doi-asserted-by":"publisher","first-page":"5944","DOI":"10.1109\/TIP.2021.3090531","volume":"30","author":"M Scetbon","year":"2021","unstructured":"Scetbon, M., Elad, M., Milanfar, P.: Deep k-svd denoising. IEEE Trans. Image Process. 30, 5944\u20135955 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"3249_CR19","doi-asserted-by":"crossref","unstructured":"Huang, J. J., Dragotti, P. L.: A deep dictionary model for image super-resolution. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 6777\u20136781. IEEE (2018)","DOI":"10.1109\/ICASSP.2018.8461651"},{"key":"3249_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107163","volume":"100","author":"V Singhal","year":"2020","unstructured":"Singhal, V., Majumdar, A.: A domain adaptation approach to solve inverse problems in imaging via coupled deep dictionary learning. Pattern Recogn. 100, 107163 (2020)","journal-title":"Pattern Recogn."},{"key":"3249_CR21","doi-asserted-by":"publisher","first-page":"7830","DOI":"10.1109\/TIP.2021.3108907","volume":"30","author":"M Vella","year":"2021","unstructured":"Vella, M., Mota, J.F.C.: Robust single-image super-resolution via CNNs and TV-TV minimization. IEEE Trans. Image Process. 30, 7830\u20137841 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"3249_CR22","doi-asserted-by":"crossref","unstructured":"Lu, Z., Li, J., Liu, H., et al.: Transformer for single image super-resolution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 457\u2013466. (2022)","DOI":"10.1109\/CVPRW56347.2022.00061"},{"key":"3249_CR23","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.neucom.2022.01.029","volume":"479","author":"H Li","year":"2022","unstructured":"Li, H., Yang, Y., Chang, M., et al.: Srdiff: single image super-resolution with diffusion probabilistic models. Neurocomputing 479, 47\u201359 (2022)","journal-title":"Neurocomputing"},{"issue":"4","key":"3249_CR24","doi-asserted-by":"publisher","first-page":"043015","DOI":"10.1117\/1.JEI.24.4.043015","volume":"24","author":"K Singh","year":"2015","unstructured":"Singh, K., Gupta, A., Kapoor, R.: Fingerprint image super-resolution via ridge orientation-based clustered coupled sparse dictionaries. J. Electron. Imaging 24(4), 043015\u2013043015 (2015)","journal-title":"J. Electron. Imaging"},{"issue":"5","key":"3249_CR25","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1049\/iet-bmt.2016.0097","volume":"6","author":"W Bian","year":"2017","unstructured":"Bian, W., Ding, S., Xue, Y.: Fingerprint image super resolution using sparse representation with ridge pattern prior by classification coupled dictionaries. IET Biom. 6(5), 342\u2013350 (2017)","journal-title":"IET Biom."},{"issue":"3","key":"3249_CR26","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1016\/0734-189X(87)90043-0","volume":"37","author":"M Kass","year":"1987","unstructured":"Kass, M., Witkin, A.: Analyzing oriented patterns. Comput. Vis. Graphics Image Process. 37(3), 362\u2013385 (1987)","journal-title":"Comput. Vis. Graphics Image Process."},{"issue":"7","key":"3249_CR27","doi-asserted-by":"publisher","first-page":"905","DOI":"10.1109\/TPAMI.2002.1017618","volume":"24","author":"AM Bazen","year":"2002","unstructured":"Bazen, A.M., Gerez, S.H.: Systematic methods for the computation of the directional fields and singular points of fingerprints. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 905\u2013919 (2002)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3249_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.forsciint.2020.110187","volume":"309","author":"N Singla","year":"2020","unstructured":"Singla, N., Kaur, M., Sofat, S.: Automated latent fingerprint identification system: a review. Forensic Sci. Int. 309, 110187 (2020)","journal-title":"Forensic Sci. Int."},{"key":"3249_CR29","doi-asserted-by":"publisher","first-page":"2493","DOI":"10.1109\/TIFS.2023.3266625","volume":"18","author":"Y Duan","year":"2023","unstructured":"Duan, Y., Feng, J., Lu, J., et al.: Estimating fingerprint pose via dense voting. IEEE Trans. Inf. Forensics Secur. 18, 2493 (2023)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"3249_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12859-020-03857-z","volume":"21","author":"Y Tu","year":"2020","unstructured":"Tu, Y., Yao, Z., Xu, J., et al.: Fingerprint restoration using cubic Bezier curve. BMC Bioinf. 21, 1\u201319 (2020)","journal-title":"BMC Bioinf."},{"issue":"5","key":"3249_CR31","doi-asserted-by":"publisher","first-page":"1035","DOI":"10.1016\/j.compeleceng.2011.10.011","volume":"38","author":"Y Mei","year":"2012","unstructured":"Mei, Y., Cao, G., Sun, H., et al.: A systematic gradient-based method for the computation of fingerprint\u2019s orientation field. Comput. Electr. Eng. 38(5), 1035\u20131046 (2012)","journal-title":"Comput. Electr. Eng."},{"issue":"10","key":"3249_CR32","doi-asserted-by":"publisher","first-page":"3304","DOI":"10.1016\/j.patcog.2014.03.033","volume":"47","author":"W Bian","year":"2014","unstructured":"Bian, W., Luo, Y., Xu, D., et al.: Fingerprint ridge orientation field reconstruction using the best quadratic approximation by orthogonal polynomials in two discrete variables. Pattern Recogn. 47(10), 3304\u20133313 (2014)","journal-title":"Pattern Recogn."},{"issue":"10","key":"3249_CR33","doi-asserted-by":"publisher","first-page":"1441","DOI":"10.1109\/LSP.2019.2934045","volume":"26","author":"FG Veshki","year":"2019","unstructured":"Veshki, F.G., Vorobyov, S.A.: An efficient coupled dictionary learning method. IEEE Signal Process. Lett. 26(10), 1441\u20131445 (2019)","journal-title":"IEEE Signal Process. Lett."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03249-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-024-03249-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03249-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T07:25:26Z","timestamp":1732173926000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-024-03249-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,6]]},"references-count":33,"journal-issue":{"issue":"6-7","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["3249"],"URL":"https:\/\/doi.org\/10.1007\/s11760-024-03249-3","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"type":"print","value":"1863-1703"},{"type":"electronic","value":"1863-1711"}],"subject":[],"published":{"date-parts":[[2024,6,6]]},"assertion":[{"value":"14 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 April 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 April 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 June 2024","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"}}]}}