{"id":"https://openalex.org/W3048700387","doi":"https://doi.org/10.1109/tifs.2020.3015547","title":"Robust Iris Presentation Attack Detection Fusing 2D and 3D Information","display_name":"Robust Iris Presentation Attack Detection Fusing 2D and 3D Information","publication_year":2020,"publication_date":"2020-08-11","ids":{"openalex":"https://openalex.org/W3048700387","doi":"https://doi.org/10.1109/tifs.2020.3015547","mag":"3048700387"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2020.3015547","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2020.3015547","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-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":"https://openalex.org/A5102739579","display_name":"Zhaoyuan Fang","orcid":"https://orcid.org/0000-0002-6671-3279"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaoyuan Fang","raw_affiliation_strings":["University of Notre Dame, Notre Dame, USA"],"raw_orcid":"https://orcid.org/0000-0002-6671-3279","affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067121774","display_name":"Adam Czajka","orcid":"https://orcid.org/0000-0003-2379-2533"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adam Czajka","raw_affiliation_strings":["University of Notre Dame, Notre Dame, USA"],"raw_orcid":"https://orcid.org/0000-0003-2379-2533","affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019673624","display_name":"Kevin W. Bowyer","orcid":"https://orcid.org/0000-0002-7562-4390"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin W. Bowyer","raw_affiliation_strings":["University of Notre Dame, Notre Dame, USA"],"raw_orcid":"https://orcid.org/0000-0002-7562-4390","affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9539,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.9454083,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"16","issue":null,"first_page":"510","last_page":"520"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9998999834060669,"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":0.9998999834060669,"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/T11800","display_name":"User Authentication and Security Systems","score":0.9814000129699707,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10751","display_name":"Forensic and Genetic Research","score":0.9610000252723694,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8673973083496094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.736680269241333},{"id":"https://openalex.org/keywords/iris-recognition","display_name":"Iris recognition","score":0.7326065897941589},{"id":"https://openalex.org/keywords/iris","display_name":"IRIS (biosensor)","score":0.6738417148590088},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5874014496803284},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.556402862071991},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5160843729972839},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.42427337169647217},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.2483096718788147},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08999821543693542}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8673973083496094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.736680269241333},{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.7326065897941589},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.6738417148590088},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5874014496803284},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.556402862071991},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5160843729972839},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.42427337169647217},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.2483096718788147},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08999821543693542},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2020.3015547","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2020.3015547","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1502160187","https://openalex.org/W1844422699","https://openalex.org/W1845048434","https://openalex.org/W1869924930","https://openalex.org/W1879242765","https://openalex.org/W2022228241","https://openalex.org/W2024178148","https://openalex.org/W2083231836","https://openalex.org/W2150817856","https://openalex.org/W2609559115","https://openalex.org/W2627044814","https://openalex.org/W2787293095","https://openalex.org/W2809965762","https://openalex.org/W2893897946","https://openalex.org/W2907633828","https://openalex.org/W2963510365","https://openalex.org/W2964009128","https://openalex.org/W3101650140","https://openalex.org/W6630005630","https://openalex.org/W6754895985"],"related_works":["https://openalex.org/W2162640687","https://openalex.org/W2151970936","https://openalex.org/W2759939383","https://openalex.org/W2557390811","https://openalex.org/W2355560018","https://openalex.org/W2147209541","https://openalex.org/W4231710054","https://openalex.org/W3213945064","https://openalex.org/W3133795085","https://openalex.org/W2952386695"],"abstract_inverted_index":{"Diversity":[0],"and":[1,34,74,164,183,200],"unpredictability":[2],"of":[3,22,37,45,53,77,121,130,137],"artifacts":[4,54],"potentially":[5],"presented":[6],"to":[7,20,41,81,126,144,155],"an":[8,75],"iris":[9,40,60,89,116,133,190],"sensor":[10],"calls":[11],"for":[12],"presentation":[13,23],"attack":[14,24],"detection":[15,47],"methods":[16,192],"that":[17,31,171,184],"are":[18,55,62,91,205],"agnostic":[19],"specificity":[21],"instruments.":[25],"This":[26],"article":[27],"proposes":[28],"a":[29,65,94,147,151,165],"method":[30,67,97,174],"combines":[32],"two-dimensional":[33],"three-dimensional":[35],"properties":[36,52],"the":[38,43,128,131,172,201],"observed":[39,132],"address":[42],"problem":[44],"spoof":[46],"in":[48,112,194],"case":[49],"when":[50],"some":[51],"unknown.":[56],"The":[57,86,119,135,197],"2D":[58,83],"(textural)":[59],"features":[61,90],"extracted":[63],"by":[64,93],"state-of-the-art":[66],"employing":[68],"Binary":[69],"Statistical":[70],"Image":[71],"Features":[72],"(BSIF)":[73],"ensemble":[76],"classifiers":[78],"is":[79,124,149,175],"used":[80,125],"deliver":[82],"modality-related":[84],"decision.":[85],"3D":[87],"(shape)":[88],"reconstructed":[92],"photometric":[95],"stereo":[96],"from":[98],"only":[99],"two":[100,108,139],"images":[101],"captured":[102],"under":[103,178],"near-infrared":[104],"illumination":[105],"placed":[106],"at":[107],"different":[109],"angles,":[110],"as":[111],"many":[113],"current":[114],"commercial":[115],"recognition":[117],"sensors.":[118],"map":[120],"normal":[122],"vectors":[123],"assess":[127],"convexity":[129],"surface.":[134],"combination":[136],"these":[138],"approaches":[140],"has":[141],"been":[142],"applied":[143],"detect":[145],"whether":[146],"subject":[148],"wearing":[150],"textured":[152],"contact":[153],"lens":[154],"disguise":[156],"their":[157],"identity.":[158],"Extensive":[159],"experiments":[160],"with":[161,209],"NDCLD'15":[162],"dataset,":[163],"newly":[166,202],"collected":[167],"NDIris3D":[168],"dataset":[169],"show":[170],"proposed":[173],"highly":[176],"robust":[177],"various":[179],"open-set":[180],"testing":[181],"scenarios,":[182],"it":[185],"outperforms":[186],"all":[187],"available":[188,207],"open-source":[189],"PAD":[191],"tested":[193],"identical":[195],"scenarios.":[196],"source":[198],"code":[199],"prepared":[203],"benchmark":[204],"made":[206],"along":[208],"this":[210],"article.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
