{"id":"https://openalex.org/W2433590983","doi":"https://doi.org/10.1109/ncvpripg.2015.7490064","title":"Tri-modal biometric fusion for human authentication by tracking Differential Code Pattern","display_name":"Tri-modal biometric fusion for human authentication by tracking Differential Code Pattern","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2433590983","doi":"https://doi.org/10.1109/ncvpripg.2015.7490064","mag":"2433590983"},"language":"en","primary_location":{"id":"doi:10.1109/ncvpripg.2015.7490064","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncvpripg.2015.7490064","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","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":"https://openalex.org/A5103245984","display_name":"Aditya Nigam","orcid":"https://orcid.org/0000-0003-4755-0619"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Aditya Nigam","raw_affiliation_strings":["School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, India"],"affiliations":[{"raw_affiliation_string":"School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100541144","display_name":"Phalguni Gupta","orcid":null},"institutions":[{"id":"https://openalex.org/I4210094264","display_name":"National Institute of Technical Teachers\u2019 Training and Research","ror":"https://ror.org/00k8f0f41","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210094264"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Phalguni Gupta","raw_affiliation_strings":["CSE Department, NITTTR, Kolkata, Salt Lake, India"],"affiliations":[{"raw_affiliation_string":"CSE Department, NITTTR, Kolkata, Salt Lake, India","institution_ids":["https://openalex.org/I4210094264"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103245984"],"corresponding_institution_ids":["https://openalex.org/I9579091"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.23798974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":1.0,"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":1.0,"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":0.9934999942779541,"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/T11448","display_name":"Face recognition and analysis","score":0.9854999780654907,"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/biometrics","display_name":"Biometrics","score":0.7615085244178772},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7158214449882507},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6489614248275757},{"id":"https://openalex.org/keywords/authentication","display_name":"Authentication (law)","score":0.6428617238998413},{"id":"https://openalex.org/keywords/knuckle","display_name":"Knuckle","score":0.6218780279159546},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5776466131210327},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5323702692985535},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.524417519569397},{"id":"https://openalex.org/keywords/iris","display_name":"IRIS (biosensor)","score":0.5064712762832642},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48917797207832336},{"id":"https://openalex.org/keywords/iris-recognition","display_name":"Iris recognition","score":0.4754219353199005},{"id":"https://openalex.org/keywords/palm-print","display_name":"Palm print","score":0.43494781851768494},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.41250842809677124},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16423773765563965},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16400480270385742},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.07358810305595398}],"concepts":[{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.7615085244178772},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7158214449882507},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6489614248275757},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.6428617238998413},{"id":"https://openalex.org/C2775868079","wikidata":"https://www.wikidata.org/wiki/Q794715","display_name":"Knuckle","level":2,"score":0.6218780279159546},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5776466131210327},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5323702692985535},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.524417519569397},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.5064712762832642},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48917797207832336},{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.4754219353199005},{"id":"https://openalex.org/C2777503689","wikidata":"https://www.wikidata.org/wiki/Q7128108","display_name":"Palm print","level":3,"score":0.43494781851768494},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.41250842809677124},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16423773765563965},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16400480270385742},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.07358810305595398},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ncvpripg.2015.7490064","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncvpripg.2015.7490064","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W41316734","https://openalex.org/W91726925","https://openalex.org/W597715780","https://openalex.org/W1464873256","https://openalex.org/W1578180497","https://openalex.org/W1760485110","https://openalex.org/W1818724389","https://openalex.org/W1976816431","https://openalex.org/W2017216471","https://openalex.org/W2025546194","https://openalex.org/W2034425991","https://openalex.org/W2054595933","https://openalex.org/W2069320147","https://openalex.org/W2105544530","https://openalex.org/W2116644114","https://openalex.org/W2118877769","https://openalex.org/W2130103520","https://openalex.org/W2133693315","https://openalex.org/W2171596602","https://openalex.org/W6677548441","https://openalex.org/W6679388247"],"related_works":["https://openalex.org/W2045898839","https://openalex.org/W2162640687","https://openalex.org/W2018223046","https://openalex.org/W2151970936","https://openalex.org/W2759939383","https://openalex.org/W2294693339","https://openalex.org/W2557390811","https://openalex.org/W2355560018","https://openalex.org/W2147209541","https://openalex.org/W3133795085"],"abstract_inverted_index":{"Human":[0],"authentication":[1,16],"can":[2],"now":[3],"be":[4],"seen":[5],"as":[6],"a":[7,14],"crucial":[8],"social":[9],"problem.":[10],"In":[11],"this":[12],"paper":[13],"multimodal":[15,94],"system":[17,62,83],"is":[18,21],"presented":[19],"which":[20],"highly":[22],"reliable":[23],"and":[24,28,69,74,76],"fuses":[25],"iris,":[26,71],"finger-knuckle-print":[27,73],"palmprint":[29],"image":[30],"matching":[31],"scores.":[32],"Segmented":[33],"ROI":[34],"are":[35,49],"preprocessed":[36],"using":[37,51],"DCP":[38],"(Differential":[39],"Code":[40],"Pattern)":[41],"to":[42],"obtain":[43],"robust":[44],"corner":[45],"features.":[46],"Later":[47],"they":[48],"matched":[50],"the":[52],"GOF":[53],"(Global":[54],"Optical":[55],"Flow)":[56],"based":[57],"dissimilarity":[58],"measure.":[59],"The":[60,81],"proposed":[61,82],"has":[63,84,101],"been":[64],"tested":[65],"on":[66],"Casia":[67,77],"Interval":[68],"Lamp":[70],"PolyU":[72,75],"palmprint,":[78],"public":[79],"databases.":[80],"shown":[85,102],"good":[86],"performance":[87,104],"over":[88,93],"all":[89,97],"unimodal":[90],"databases":[91,99],"while":[92],"(fusion":[95],"of":[96],"three)":[98],"it":[100],"perfect":[103],"(i.e.":[105],"CRR":[106],"=":[107,111],"100%":[108],"with":[109],"EER":[110],"0%).":[112]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
