{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T11:08:27Z","timestamp":1788865707996,"version":"build-2803163510"},"reference-count":62,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61906153"],"award-info":[{"award-number":["61906153"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["61906153"],"award-info":[{"award-number":["61906153"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007128","name":"Natural Science Foundation of Shaanxi Province","doi-asserted-by":"publisher","award":["2020JQ-651"],"award-info":[{"award-number":["2020JQ-651"]}],"id":[{"id":"10.13039\/501100007128","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>This paper proposes Phase-PCANet, a new image representation method for fingerprint liveness detection. Phase-PCANet integrates both local and global phase features. The local phase, capturing fine-grained edges and textures, is extracted via short-time Fourier transform with singular value decomposition; the global phase, encoding the holistic structural layout, is obtained from a full-image Fourier transform. These two phase components are separately fed into an improved PCANet, which employs dual binary coding, i.e., scalar-based intra-channel coding and vector-similarity-based inter-channel coding, to preserve within-channel structures and cross-channel correlations. Multi-stage features from different PCA layers within each phase path are aggregated, and the resulting deep features from both paths are concatenated to form the final image representation. Experiments on the LivDet 2011, 2013, and 2015 databases verify the effectiveness of the proposed method.<\/jats:p>","DOI":"10.3390\/jimaging12090422","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T10:00:04Z","timestamp":1788861604000},"page":"422","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Phase-PCANet for Fingerprint Image Liveness Detection"],"prefix":"10.3390","volume":"12","author":[{"given":"Jing","family":"Li","sequence":"first","affiliation":[{"name":"Information Science Department, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Xinqi","family":"Wang","sequence":"additional","affiliation":[{"name":"Information Science Department, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"software","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1109\/PROC.1981.12022","article-title":"The importance of phase in signals","volume":"69","author":"Oppenheim","year":"1981","journal-title":"Proc. IEEE"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1268","DOI":"10.1049\/el.2010.1549","article-title":"Automatic detection of active sweat pores of fingerprint using highpass and correlation filtering","volume":"46","author":"Manivanan","year":"2010","journal-title":"Electron. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Espinoza, M., and Champod, C. (2011, January 17\u201318). Using the number of pores on fingerprint images to detect spoofing attacks. Proceedings of the International Conference on Hand-Based Biometrics, Hong Kong, China.","DOI":"10.1109\/ICHB.2011.6094347"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Lu, M., Chen, Z., and Sheng, W. (2015). Fingerprint liveness detection based on pore analysis. Chinese Conference on Biometric Recognition, Springer International Publishing.","DOI":"10.1007\/978-3-319-25417-3_28"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1109\/TIFS.2006.879289","article-title":"Fake finger detection by skin distortion analysis","volume":"1","author":"Antonelli","year":"2006","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Tian, J., Chen, X., Yang, X., and Shi, P. (2007). Fake finger detection based on thin-plate spline distortion model. International Conference on Biometrics, Springer.","DOI":"10.1007\/978-3-540-74549-5_78"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Jia, J., Cai, L., Zhang, K., and Chen, D. (2007). A new approach to fake finger detection based on skin elasticity analysis. International Conference on Biometrics, Springer.","DOI":"10.1007\/978-3-540-74549-5_33"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1016\/j.patcog.2008.06.012","article-title":"Integrating a wavelet based perspiration liveness check with fingerprint recognition","volume":"42","author":"Abhyankar","year":"2009","journal-title":"Pattern Recognit."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Abhyankar, A., and Schuckers, S. (2006, January 8\u201311). Fingerprint liveness detection using local ridge frequencies and multiresolution texture analysis techniques. Proceedings of the IEEE International Conference on Image Processing, Atlanta, GA, USA.","DOI":"10.1109\/ICIP.2006.313158"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.future.2010.11.024","article-title":"A high performance fingerprint liveness detection method based on quality related features","volume":"28","author":"Galbally","year":"2012","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4175","DOI":"10.1007\/s00500-017-2707-3","article-title":"Statistical anti-spoofing method for fingerprint recognition","volume":"22","author":"Park","year":"2018","journal-title":"Soft Comput."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1393","DOI":"10.1007\/s00371-018-01618-x","article-title":"Fingerprint liveness detection using local quality features","volume":"35","author":"Sharma","year":"2018","journal-title":"Vis. Comput."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"5157","DOI":"10.1007\/s00500-018-3182-1","article-title":"Difference co-occurrence matrix using bp neural network for fingerprint liveness detection","volume":"23","author":"Yuan","year":"2018","journal-title":"Soft Comput."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1112","DOI":"10.1049\/el:20052577","article-title":"Wavelet based fingerprint liveness detection","volume":"41","author":"Moon","year":"2005","journal-title":"Electron. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1049\/el.2012.4173","article-title":"Spatial surface coarseness analysis: Technique for fingerprint spoof detection","volume":"49","author":"Pereira","year":"2013","journal-title":"Electron. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2491","DOI":"10.1016\/j.neucom.2008.11.003","article-title":"Ridgelet-based fake fingerprint detection","volume":"72","author":"Nikam","year":"2009","journal-title":"Neurocomputing"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s11760-008-0098-8","article-title":"Curvelet-based fingerprint anti-spoofing","volume":"4","author":"Nikam","year":"2009","journal-title":"Signal Image Video Process."},{"key":"ref_18","unstructured":"Ghiani, L., Marcialis, G.L., and Roli, F. (2012, January 11\u201315). Fingerprint liveness detection by local phase quantization. Proceedings of the International Conference on Pattern Recognition, Tsukuba, Japan."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.ins.2013.06.041","article-title":"Multi-scale local binary pattern with filters for spoof fingerprint detection","volume":"268","author":"Jia","year":"2014","journal-title":"Inf. Sci."},{"key":"ref_20","unstructured":"Gottschlich, C., Marasco, E., Yang, A.Y., and Cukic, B. (October, January 29). Fingerprint liveness detection based on histograms of invariant gradients. Proceedings of the IEEE International Joint Conference on Biometrics, Clearwater, FL, USA."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Fang, S., Xie, Y., and Xu, T. (2014). Fake fingerprint detection based on wavelet analysis and local binary pattern. Chinese Conference on Biometric Recognition, Springer International Publishing.","DOI":"10.1007\/978-3-319-12484-1_21"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1049\/el.2013.4044","article-title":"Wavelet-markov local descriptor for detecting fake fingerprints","volume":"50","author":"Gragnaniello","year":"2014","journal-title":"Electron. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Rattani, A., and Ross, A. (2014, January 7\u201330). Minimizing the impact of spoof fabrication material on fingerprint liveness detector. Proceedings of the IEEE International Conference on Image Processing, Paris, France.","DOI":"10.1109\/ICIP.2014.7026011"},{"key":"ref_24","unstructured":"Rattani, A., and Ross, A. (October, January 29). Automatic adaptation of fingerprint liveness detector to new spoof materials. Proceedings of the IEEE International Joint Conference on Biometrics, Clearwater, FL, USA."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1050","DOI":"10.1016\/j.patcog.2014.05.021","article-title":"Local contrast phase descriptor for fingerprint liveness detection","volume":"48","author":"Gragnaniello","year":"2015","journal-title":"Pattern Recognit."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1461","DOI":"10.1109\/TIFS.2016.2535899","article-title":"Fingerprint liveness detection from single image using low-level features and shape analysis","volume":"11","author":"Dubey","year":"2016","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1007\/s11760-016-0936-z","article-title":"Fingerprint liveness detection using gradient-based texture features","volume":"11","author":"Xia","year":"2016","journal-title":"Signal Image Video Process."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"18187","DOI":"10.1007\/s11042-017-5517-9","article-title":"Rotation-invariant weber pattern and gabor feature for fingerprint liveness detection","volume":"77","author":"Xia","year":"2017","journal-title":"Multimed. Tools Appl."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1109\/LSP.2016.2636158","article-title":"Fingerprint liveness detection using local coherence patterns","volume":"24","author":"Kim","year":"2017","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1049\/iet-bmt.2016.0007","article-title":"Fingerprint liveness detection using local texture features","volume":"6","author":"Ghiani","year":"2017","journal-title":"IET Biom."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"053038","DOI":"10.1117\/1.JEI.27.5.053038","article-title":"Live fingerprint detection using magnitude of perceived spatial stimuli and local phase information","volume":"27","author":"Mehboob","year":"2018","journal-title":"J. Electron. Imaging"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"102039","DOI":"10.1016\/j.bspc.2020.102039","article-title":"Exploiting level 1 and level 3 features of fingerprints for liveness detection","volume":"61","author":"Alshdadi","year":"2020","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"5806","DOI":"10.1109\/ACCESS.2020.3048756","article-title":"Fingerprint presentation attack detection based on local features encoding for unknown attacks","volume":"9","author":"Chang","year":"2021","journal-title":"IEEE Access"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2999","DOI":"10.1007\/s00371-021-02173-8","article-title":"Hyfipad: A hybrid approach for fingerprint presentation attack detection using local and adaptive image features","volume":"38","author":"Sharma","year":"2021","journal-title":"Vis. Comput."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"22129","DOI":"10.1007\/s11042-021-11254-8","article-title":"An intelligent approach for fingerprint presentation attack detection using ensemble learning with improved local image features","volume":"81","author":"Sharma","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"4089","DOI":"10.1016\/j.jksuci.2020.10.003","article-title":"Fingerprint liveness detection through fusion of pores perspiration and texture features","volume":"34","author":"Agarwal","year":"2022","journal-title":"J. King Saud Univ.-Comput. Inf. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"103572","DOI":"10.1016\/j.bspc.2022.103572","article-title":"DEHFF\u2014A hybrid approach based on distinctively encoded fingerprint features for live fingerprint detection","volume":"75","author":"Mehboob","year":"2022","journal-title":"Biomed. Process. Control"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1109\/LSP.2023.3293471","article-title":"Deepfake fingerprint detection model intellectual property protection via ridge texture enhancement","volume":"30","author":"Yuan","year":"2023","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"864","DOI":"10.1109\/TIFS.2015.2398817","article-title":"Deep representations for iris, face, and fingerprint spoofing detection","volume":"10","author":"Menotti","year":"2015","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.patrec.2016.03.015","article-title":"Deep belief network based statistical feature learning for fingerprint liveness detection","volume":"77","author":"Kim","year":"2016","journal-title":"Pattern Recognit. Lett."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"183391","DOI":"10.1109\/ACCESS.2020.3027846","article-title":"A score-level fusion of fingerprint matching with fingerprint liveness detection","volume":"8","author":"Zhang","year":"2020","journal-title":"IEEE Access"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"648","DOI":"10.1109\/TCDS.2021.3062624","article-title":"Mfffld: A multimodal-feature-fusion-based fingerprint liveness detection","volume":"14","author":"Yuan","year":"2022","journal-title":"IEEE Trans. Cogn. Dev. Syst."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Kothadiya, D., Bhatt, C., Soni, D., Gadhe, K., Patel, S., Bruno, A., and Mazzeo, P.L. (2023). Enhancing fingerprint liveness detection accuracy using deep learning: A comprehensive study and novel approach. J. Imaging, 9.","DOI":"10.3390\/jimaging9080158"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Zhang, K., Huang, S., Liu, E., and Zhao, H. (2023). Lfldnet: Lightweight fingerprint liveness detection based on resnet and transformer. Sensors, 23.","DOI":"10.3390\/s23156854"},{"key":"ref_45","unstructured":"Yambay, D., Ghiani, L., Denti, P., Marcialis, G.L., Roli, F., and Schuckers, S. (April, January 29). Livdet 2011\u2014Fingerprint liveness detection competition 2011. Proceedings of the IAPR International Conference on Biometrics, New Delhi, India."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Ghiani, L., Yambay, D., Mura, V., Tocco, S., Marcialis, G.L., Roli, F., and Schuckcrs, S. (2013, January 4\u20137). Livdet 2013 fingerprint liveness detection competition 2013. Proceedings of the International Conference on Biometrics, Madrid, Spain.","DOI":"10.1109\/ICB.2013.6613027"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Mura, V., Ghiani, L., Marcialis, G.L., Roli, F., Yambay, D.A., and Schuckers, S.A. (2015, January 8\u201311). Livdet 2015 fingerprint liveness detection competition 2015. Proceedings of the IEEE International Conference on Biometrics Theory, Applications and Systems, Arlington, VA, USA.","DOI":"10.1109\/BTAS.2015.7358776"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1526","DOI":"10.1109\/TSMC.2018.2874281","article-title":"A novel weber local binary descriptor for fingerprint liveness detection","volume":"50","author":"Xia","year":"2020","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Gragnaniello, D., Poggi, G., Sansone, C., and Verdoliva, L. (2013, January 9). Fingerprint liveness detection based on weber local image descriptor. Proceedings of the IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications, Napoli, Italy.","DOI":"10.1109\/BIOMS.2013.6656148"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1422","DOI":"10.1587\/transinf.2019EDL8044","article-title":"Weber centralized binary fusion descriptor for fingerprint liveness detection","volume":"E102.D","author":"Asera","year":"2019","journal-title":"IEICE Trans. Inf. Syst."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"116603","DOI":"10.1016\/j.image.2021.116603","article-title":"Comprehensive edge direction descriptor for fingerprint liveness detection","volume":"102","author":"Li","year":"2022","journal-title":"Signal Process. Image Commun."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"8229","DOI":"10.1007\/s11760-024-03466-w","article-title":"Striver: An image descriptor for fingerprint liveness detection","volume":"18","author":"Li","year":"2024","journal-title":"Signal Image Video Process."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1109\/TIFS.2015.2404294","article-title":"An investigation of local descriptors for biometric spoofing detection","volume":"10","author":"Gragnaniello","year":"2015","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2229","DOI":"10.1109\/ACCESS.2020.3047723","article-title":"Densely connected convolutional network optimized by genetic algorithm for fingerprint liveness detection","volume":"9","author":"Jian","year":"2021","journal-title":"IEEE Access"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"9993","DOI":"10.1007\/s11042-020-10136-9","article-title":"A comparative study of handcrafted local texture descriptors for fingerprint liveness detection under real world scenarios","volume":"80","author":"Sharma","year":"2020","journal-title":"Multimed. Tools Appl."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1109\/TCDS.2019.2920364","article-title":"Deep residual network with adaptive learning framework for fingerprint liveness detection","volume":"12","author":"Yuan","year":"2020","journal-title":"IEEE Trans. Cogn. Dev. Syst."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1206","DOI":"10.1109\/TIFS.2016.2520880","article-title":"Fingerprint liveness detection using convolutional neural networks","volume":"11","author":"Nogueira","year":"2016","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"817","DOI":"10.1109\/JSTSP.2022.3174655","article-title":"Fld-src: Fingerprint liveness detection for afis based on spatial ridges continuity","volume":"16","author":"Yuan","year":"2022","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_59","first-page":"1","article-title":"Image features from phase congruency","volume":"1","author":"Kovesi","year":"1999","journal-title":"Videre J. Comput. Res."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Tian, Y., Wen, M., Lu, D., Zhong, X., and Wu, Z. (2024). Biological basis and computer vision applications of image phase congruency: A comprehensive survey. Biomimetics, 9.","DOI":"10.3390\/biomimetics9070422"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/bs.adcom.2023.04.004","article-title":"Chapter four\u2014A realtime fingerprint liveness detection method for fingerprint authentication systems","volume":"Volume 131","author":"Yuan","year":"2023","journal-title":"Advances in Computers"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"106256","DOI":"10.1016\/j.autcon.2025.106256","article-title":"Transformer-based large vision model for universal structural damage segmentation","volume":"176","author":"Xu","year":"2025","journal-title":"Autom. 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