{"id":"https://openalex.org/W7133341303","doi":"https://doi.org/10.1109/ijcb65343.2025.11411223","title":"Improving Contactless Fingerprint Recognition with Robust 3D Feature Extraction and Graph Embedding","display_name":"Improving Contactless Fingerprint Recognition with Robust 3D Feature Extraction and Graph Embedding","publication_year":2025,"publication_date":"2025-09-08","ids":{"openalex":"https://openalex.org/W7133341303","doi":"https://doi.org/10.1109/ijcb65343.2025.11411223"},"language":null,"primary_location":{"id":"doi:10.1109/ijcb65343.2025.11411223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11411223","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yuwei Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuwei Jia","raw_affiliation_strings":["Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Siyang Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyang Zheng","raw_affiliation_strings":["Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101041935","display_name":"Fei Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Feng","raw_affiliation_strings":["Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126137797","display_name":"Zhe Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Cui","raw_affiliation_strings":["Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101431607","display_name":"Fei Su","orcid":"https://orcid.org/0000-0002-4753-4283"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Su","raw_affiliation_strings":["Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.66301218,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.8851000070571899,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.8851000070571899,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13192","display_name":"Forensic Fingerprint Detection Methods","score":0.01590000092983246,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.014800000004470348,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.7839000225067139},{"id":"https://openalex.org/keywords/fingerprint-recognition","display_name":"Fingerprint recognition","score":0.7602999806404114},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.654699981212616},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.570900022983551},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5529000163078308},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5333999991416931},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5067999958992004},{"id":"https://openalex.org/keywords/minutiae","display_name":"Minutiae","score":0.45399999618530273}],"concepts":[{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.7839000225067139},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.7602999806404114},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7067000269889832},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.654699981212616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6287999749183655},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.570900022983551},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5529000163078308},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5333999991416931},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5087000131607056},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5067999958992004},{"id":"https://openalex.org/C67174900","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Minutiae","level":4,"score":0.45399999618530273},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3817000091075897},{"id":"https://openalex.org/C61455927","wikidata":"https://www.wikidata.org/wiki/Q1030529","display_name":"Blossom algorithm","level":3,"score":0.3425000011920929},{"id":"https://openalex.org/C180863505","wikidata":"https://www.wikidata.org/wiki/Q5439687","display_name":"Feature recognition","level":3,"score":0.34130001068115234},{"id":"https://openalex.org/C164995936","wikidata":"https://www.wikidata.org/wiki/Q5450283","display_name":"Fingerprint Verification Competition","level":4,"score":0.3280999958515167},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.2799000144004822},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.27619999647140503},{"id":"https://openalex.org/C68859911","wikidata":"https://www.wikidata.org/wiki/Q1503724","display_name":"Pattern matching","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2531999945640564},{"id":"https://openalex.org/C3019308078","wikidata":"https://www.wikidata.org/wiki/Q229367","display_name":"3d printed","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcb65343.2025.11411223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11411223","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W100001351","https://openalex.org/W435670374","https://openalex.org/W1573795313","https://openalex.org/W1963624486","https://openalex.org/W1970405634","https://openalex.org/W1986279370","https://openalex.org/W2014203677","https://openalex.org/W2014470493","https://openalex.org/W2051294001","https://openalex.org/W2064783536","https://openalex.org/W2096733369","https://openalex.org/W2113518339","https://openalex.org/W2126870276","https://openalex.org/W2130194416","https://openalex.org/W2153717930","https://openalex.org/W2156513857","https://openalex.org/W2210638116","https://openalex.org/W2534167378","https://openalex.org/W2536925565","https://openalex.org/W2767425316","https://openalex.org/W2767596693","https://openalex.org/W2782304390","https://openalex.org/W2786036168","https://openalex.org/W2876459260","https://openalex.org/W2907492528","https://openalex.org/W2963012812","https://openalex.org/W2963165122","https://openalex.org/W2979750740","https://openalex.org/W2985720528","https://openalex.org/W2990045899","https://openalex.org/W3006568837","https://openalex.org/W3033290794","https://openalex.org/W3034473953","https://openalex.org/W3157057872","https://openalex.org/W3186289373","https://openalex.org/W3186376479","https://openalex.org/W3209427996","https://openalex.org/W4205428640","https://openalex.org/W4236844882","https://openalex.org/W4295907364","https://openalex.org/W4313434180","https://openalex.org/W4313485571","https://openalex.org/W4313547860","https://openalex.org/W4323022554","https://openalex.org/W4383890556","https://openalex.org/W4386076206","https://openalex.org/W4389777434","https://openalex.org/W4392411897","https://openalex.org/W4404239035"],"related_works":[],"abstract_inverted_index":{"Contactless":[0],"fingerprint":[1,9,15,61,98,145,185],"has":[2],"gained":[3],"lots":[4],"of":[5,38,70,140,157,168],"attention":[6],"in":[7,52],"recent":[8],"studies.":[10],"However,":[11],"most":[12],"existing":[13],"contactless":[14,18,43,53,60,71,89,132,144,158,169,184],"algorithms":[16],"treat":[17],"fingerprints":[19,30,72,133,170],"as":[20],"2D":[21,29,77],"plain":[22,76],"fingerprints,":[23,46],"and":[24,44,96],"still":[25],"utilize":[26],"traditional":[27],"contact-based":[28],"recognition":[31,34,62,186],"methods.":[32],"This":[33,55],"approach":[35],"lacks":[36],"consideration":[37],"the":[39,48,66,75,87,92,114,119,141,149,154],"modality":[40],"difference":[41],"between":[42],"contact":[45],"especially":[47],"intrinsic":[49],"3D":[50,68,84,93,97,106,116,127,173],"features":[51,85],"fingerprints.":[54,159],"paper":[56],"proposes":[57],"a":[58,104,177],"novel":[59,105],"algorithm":[63],"that":[64,148],"captures":[65],"revealed":[67],"feature":[69,99,128],"rather":[73],"than":[74],"feature.":[78,117],"The":[79,138],"proposed":[80,111,120,150],"method":[81,109,121,151,162],"first":[82],"recovers":[83],"from":[86],"input":[88],"fingerprint,":[90],"including":[91],"shape":[94],"model":[95],"(minutiae,":[100],"orientation,":[101],"etc.).":[102],"Then,":[103],"graph":[107],"matching":[108,155],"is":[110,122,176],"according":[112],"to":[113,124,172,181],"extracted":[115],"Additionally,":[118],"able":[123],"perform":[125],"robust":[126],"extractions":[129],"on":[130,143],"various":[131],"across":[134,165],"multiple":[135,166],"finger":[136],"poses.":[137],"results":[139],"experiments":[142],"databases":[146],"show":[147],"successfully":[152],"improves":[153],"accuracy":[156],"Exceptionally,":[160],"our":[161],"performs":[163],"stably":[164],"poses":[167],"due":[171],"embeddings,":[174],"which":[175],"great":[178],"advantage":[179],"compared":[180],"2D-based":[182],"previous":[183],"algorithms.":[187]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-04T00:00:00"}
