{"id":"https://openalex.org/W2520287285","doi":"https://doi.org/10.1109/tifs.2016.2606083","title":"Optimal Generation of Iris Codes for Iris Recognition","display_name":"Optimal Generation of Iris Codes for Iris Recognition","publication_year":2016,"publication_date":"2016-09-15","ids":{"openalex":"https://openalex.org/W2520287285","doi":"https://doi.org/10.1109/tifs.2016.2606083","mag":"2520287285"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2016.2606083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2016.2606083","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/A5059343235","display_name":"Yang Hu","orcid":"https://orcid.org/0000-0003-2388-7719"},"institutions":[{"id":"https://openalex.org/I20581793","display_name":"University of Kent","ror":"https://ror.org/00xkeyj56","country_code":"GB","type":"education","lineage":["https://openalex.org/I20581793"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Yang Hu","raw_affiliation_strings":["School of Engineering and Digital Arts, University of Kent, Canterbury, U.K"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Digital Arts, University of Kent, Canterbury, U.K","institution_ids":["https://openalex.org/I20581793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055586446","display_name":"Konstantinos Sirlantzis","orcid":"https://orcid.org/0000-0002-0847-8880"},"institutions":[{"id":"https://openalex.org/I20581793","display_name":"University of Kent","ror":"https://ror.org/00xkeyj56","country_code":"GB","type":"education","lineage":["https://openalex.org/I20581793"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Konstantinos Sirlantzis","raw_affiliation_strings":["School of Engineering and Digital Arts, University of Kent, Canterbury, U.K"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Digital Arts, University of Kent, Canterbury, U.K","institution_ids":["https://openalex.org/I20581793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059301513","display_name":"Gareth Howells","orcid":"https://orcid.org/0000-0001-5590-0880"},"institutions":[{"id":"https://openalex.org/I20581793","display_name":"University of Kent","ror":"https://ror.org/00xkeyj56","country_code":"GB","type":"education","lineage":["https://openalex.org/I20581793"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gareth Howells","raw_affiliation_strings":["School of Engineering and Digital Arts, University of Kent, Canterbury, U.K"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Digital Arts, University of Kent, Canterbury, U.K","institution_ids":["https://openalex.org/I20581793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059343235"],"corresponding_institution_ids":["https://openalex.org/I20581793"],"apc_list":null,"apc_paid":null,"fwci":3.7827,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.94283673,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"12","issue":"1","first_page":"157","last_page":"171"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9998000264167786,"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":0.9998000264167786,"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/T10057","display_name":"Face and Expression Recognition","score":0.9937000274658203,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9904999732971191,"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/iris-recognition","display_name":"Iris recognition","score":0.8889319896697998},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7728085517883301},{"id":"https://openalex.org/keywords/iris","display_name":"IRIS (biosensor)","score":0.7183829545974731},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6870364546775818},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.633274495601654},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.6208012104034424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5499781370162964},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5285683274269104},{"id":"https://openalex.org/keywords/binary-code","display_name":"Binary code","score":0.4976074993610382},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4485796093940735},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4397830665111542},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35568487644195557},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32112643122673035},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.286896288394928},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18961530923843384}],"concepts":[{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.8889319896697998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7728085517883301},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.7183829545974731},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6870364546775818},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.633274495601654},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.6208012104034424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5499781370162964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5285683274269104},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.4976074993610382},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4485796093940735},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4397830665111542},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35568487644195557},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32112643122673035},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.286896288394928},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18961530923843384},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tifs.2016.2606083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2016.2606083","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"},{"id":"pmh:oai:kar.kent.ac.uk:58277","is_oa":false,"landing_page_url":"https://doi.org/10.1109/TIFS.2016.2606083>)","pdf_url":null,"source":{"id":"https://openalex.org/S4377196264","display_name":"Kent Academic Repository (University of Kent)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I20581793","host_organization_name":"University of Kent","host_organization_lineage":["https://openalex.org/I20581793"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W157158741","https://openalex.org/W1510216433","https://openalex.org/W1967831779","https://openalex.org/W1970913757","https://openalex.org/W1971189077","https://openalex.org/W1974821667","https://openalex.org/W1977095724","https://openalex.org/W1985110735","https://openalex.org/W1995054709","https://openalex.org/W2015362166","https://openalex.org/W2017635038","https://openalex.org/W2022864356","https://openalex.org/W2023296739","https://openalex.org/W2024264463","https://openalex.org/W2025546194","https://openalex.org/W2027591525","https://openalex.org/W2028354897","https://openalex.org/W2039458866","https://openalex.org/W2071367353","https://openalex.org/W2094333869","https://openalex.org/W2096139825","https://openalex.org/W2100603595","https://openalex.org/W2102525097","https://openalex.org/W2102796633","https://openalex.org/W2103017672","https://openalex.org/W2115718877","https://openalex.org/W2117640672","https://openalex.org/W2117721235","https://openalex.org/W2133295669","https://openalex.org/W2143516773","https://openalex.org/W2146142639","https://openalex.org/W2149999708","https://openalex.org/W2152413067","https://openalex.org/W2155410395","https://openalex.org/W2157236671","https://openalex.org/W2160242612","https://openalex.org/W2161087606","https://openalex.org/W2161703452","https://openalex.org/W2164598857","https://openalex.org/W2168567026","https://openalex.org/W2169096120","https://openalex.org/W2171759622","https://openalex.org/W2212252382","https://openalex.org/W2317989223","https://openalex.org/W2547391922","https://openalex.org/W2606090080","https://openalex.org/W6606412717","https://openalex.org/W6630550317","https://openalex.org/W6675513886","https://openalex.org/W6683645654","https://openalex.org/W6736677744"],"related_works":["https://openalex.org/W2609035398","https://openalex.org/W2373529582","https://openalex.org/W2370714421","https://openalex.org/W2889989850","https://openalex.org/W276445467","https://openalex.org/W2204049424","https://openalex.org/W3008151551","https://openalex.org/W2119197518","https://openalex.org/W2127677160","https://openalex.org/W2546942002"],"abstract_inverted_index":{"The":[0,123,141,155,183],"calculation":[1,63],"of":[2,12,30,67,79,113,131,137,148],"binary":[3],"iris":[4,20,53,61,74,93,101,139,153,189,213],"codes":[5,102],"from":[6,64],"feature":[7,31,89,218],"values":[8,32,90,219],"(e.g.,":[9],"the":[10,28,60,65,72,77,85,88,92,110,128,132,146,163,188,194,198,211],"result":[11],"Gabor":[13],"transform)":[14],"is":[15,76],"a":[16,44,169,204],"key":[17],"step":[18],"in":[19,134,152,168,208],"recognition":[21],"systems.":[22],"Traditional":[23],"binarization":[24,49],"method":[25,50],"based":[26,220],"on":[27,43,175,221],"sign":[29],"has":[33],"achieved":[34],"very":[35],"promising":[36],"performance.":[37],"However,":[38],"currently,":[39],"little":[40],"research":[41],"focuses":[42],"deeper":[45],"insight":[46],"into":[47],"this":[48,56,114],"to":[51,109,162,210],"produce":[52],"codes.":[54,94,154],"In":[55],"paper,":[57],"we":[58,96],"illustrate":[59],"code":[62,75,190,214],"perspective":[66],"optimization.":[68],"We":[69,117,172],"demonstrate":[70,186],"that":[71,98,187],"traditional":[73,212],"solution":[78],"an":[80,138],"optimization":[81,115,164,195],"problem,":[82],"which":[83],"minimizes":[84],"distance":[86],"between":[87],"and":[91],"Furthermore,":[95],"show":[97],"more":[99],"effective":[100],"can":[103,159],"be":[104,160],"obtained":[105],"by":[106,192,216],"adding":[107],"terms":[108,158,202],"objective":[111,121,125,143,157,201],"function":[112],"problem.":[116],"investigate":[118],"two":[119,156,199],"additional":[120,200],"terms.":[122],"first":[124],"term":[126,144],"exploits":[127],"spatial":[129],"relationships":[130],"bits":[133,151],"different":[135],"positions":[136],"code.":[140],"second":[142],"mitigates":[145],"influence":[147],"less":[149],"reliable":[150],"applied":[161],"problem":[165,196],"individually,":[166],"or":[167],"combined":[170],"scheme.":[171],"conduct":[173],"experiments":[174],"four":[176],"benchmark":[177],"datasets":[178],"with":[179,197],"varying":[180],"image":[181],"quality.":[182],"experimental":[184],"results":[185],"produced":[191],"solving":[193],"achieves":[203],"generally":[205],"improved":[206],"performance":[207],"comparison":[209],"calculated":[215],"binarizing":[217],"their":[222],"signs.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
