{"id":"https://openalex.org/W2562799543","doi":"https://doi.org/10.1109/btas.2016.7791209","title":"Which finger is the best for finger vein recognition?","display_name":"Which finger is the best for finger vein recognition?","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2562799543","doi":"https://doi.org/10.1109/btas.2016.7791209","mag":"2562799543"},"language":"en","primary_location":{"id":"doi:10.1109/btas.2016.7791209","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2016.7791209","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)","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/A5034648573","display_name":"Zheng He","orcid":"https://orcid.org/0000-0002-7700-0901"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"He Zheng","raw_affiliation_strings":["School of Electronics Engineering and Computer Science, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering and Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055043003","display_name":"Yapeng Ye","orcid":"https://orcid.org/0000-0001-7232-0650"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yapeng Ye","raw_affiliation_strings":["School of Electronics Engineering and Computer Science, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering and Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112309245","display_name":"Liao Ni","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liao Ni","raw_affiliation_strings":["School of Electronics Engineering and Computer Science, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering and Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690915","display_name":"Shilei Liu","orcid":"https://orcid.org/0000-0002-9053-8458"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shilei Liu","raw_affiliation_strings":["School of Electronics Engineering and Computer Science, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering and Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100397214","display_name":"Wenxin Li","orcid":"https://orcid.org/0000-0003-1744-7792"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxin Li","raw_affiliation_strings":["School of Electronics Engineering and Computer Science, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering and Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5034648573"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.5044,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66535668,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"12","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9997000098228455,"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":0.9997000098228455,"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/T14333","display_name":"Dermatoglyphics and Human Traits","score":0.9733999967575073,"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"}},{"id":"https://openalex.org/T11800","display_name":"User Authentication and Security Systems","score":0.9330000281333923,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.8316203355789185},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6917625665664673},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.6521950960159302},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6005098223686218},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.507982075214386},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49621278047561646},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4636569619178772},{"id":"https://openalex.org/keywords/middle-finger","display_name":"Middle finger","score":0.44739899039268494},{"id":"https://openalex.org/keywords/index-finger","display_name":"Index finger","score":0.4465765058994293},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.36534392833709717},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3261094093322754},{"id":"https://openalex.org/keywords/thumb","display_name":"Thumb","score":0.1614520251750946},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15683680772781372},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08300507068634033}],"concepts":[{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.8316203355789185},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6917625665664673},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.6521950960159302},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6005098223686218},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.507982075214386},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49621278047561646},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4636569619178772},{"id":"https://openalex.org/C2779871620","wikidata":"https://www.wikidata.org/wiki/Q167131","display_name":"Middle finger","level":3,"score":0.44739899039268494},{"id":"https://openalex.org/C2777087348","wikidata":"https://www.wikidata.org/wiki/Q184848","display_name":"Index finger","level":2,"score":0.4465765058994293},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.36534392833709717},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3261094093322754},{"id":"https://openalex.org/C2776881184","wikidata":"https://www.wikidata.org/wiki/Q83360","display_name":"Thumb","level":2,"score":0.1614520251750946},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15683680772781372},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08300507068634033},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/btas.2016.7791209","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2016.7791209","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)","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":13,"referenced_works":["https://openalex.org/W195106604","https://openalex.org/W1991620112","https://openalex.org/W2004617923","https://openalex.org/W2032476112","https://openalex.org/W2074487155","https://openalex.org/W2085194388","https://openalex.org/W2102780391","https://openalex.org/W2118323481","https://openalex.org/W2142765153","https://openalex.org/W2286640670","https://openalex.org/W4246794637","https://openalex.org/W4285719527","https://openalex.org/W6696422880"],"related_works":["https://openalex.org/W1995418324","https://openalex.org/W2211301776","https://openalex.org/W2382072760","https://openalex.org/W4240784184","https://openalex.org/W2051149807","https://openalex.org/W2370358288","https://openalex.org/W2026038451","https://openalex.org/W3175416320","https://openalex.org/W1583082339","https://openalex.org/W3180008851"],"abstract_inverted_index":{"Finger":[0],"vein":[1,9,45,89,185,267],"recognition":[2,46,90,131,186,268],"is":[3,77,110,153,166,193],"a":[4,112,122,177,200,271],"biometric":[5],"method":[6,178,192,245,260],"utilizing":[7],"the":[8,26,38,78,104,141,148,162,173,181,207,237,247,250,258,263,278],"patterns":[10],"inside":[11],"one's":[12,62],"fingers":[13,21,28,31,42,97,152,165,225,242],"for":[14,48,210],"personal":[15],"identification.":[16],"Every":[17],"user":[18,198,212],"has":[19,199],"10":[20],"in":[22,43,73,87,156,203],"total,":[23],"among":[24],"which":[25],"index":[27,96],"and":[29,34,53,133,145,159,168,206,226],"middle":[30,101],"from":[32],"left":[33],"right":[35],"hands":[36],"are":[37,67],"most":[39],"common":[40],"used":[41],"finger":[44,88,184,202,209,266],"systems,":[47],"their":[49,223,240],"suitable":[50],"length,":[51],"width":[52],"flexibility.":[54],"No":[55],"evidence":[56],"shows":[57,138],"any":[58,275],"significant":[59,272],"relationship":[60],"between":[61,80],"different":[63,71,81,127,130,134,151,155,157],"fingers,":[64,102,128],"so":[65],"they":[66,85],"usually":[68],"treated":[69],"as":[70,243],"classes":[72],"recognition.":[74],"However,":[75],"what":[76],"difference":[79],"fingers?":[82],"How":[83],"do":[84],"perform":[86,98],"systems?":[91],"Some":[92],"researchers":[93],"believe":[94],"that":[95,139,194,235],"better":[99],"than":[100],"while":[103],"others":[105],"hold":[106],"contrary":[107],"opinions.":[108],"There":[109],"not":[111],"consensus":[113],"on":[114,126,172,277],"this":[115,118],"topic.":[116],"In":[117],"paper,":[119],"we":[120,175,195,217],"conduct":[121],"set":[123],"of":[124,150,164,183,190,249,265],"experiments":[125],"with":[129],"algorithms":[132,158],"databases.":[135],"The":[136,188],"result":[137],"considering":[140],"equal":[142],"error":[143],"rate":[144],"DET":[146],"curve,":[147],"performance":[149,163,182,264],"quite":[154],"database.":[160],"Therefore":[161],"algorithm":[167,220],"database":[169],"dependent.":[170],"Based":[171],"finding,":[174],"propose":[176],"to":[179,221,229,254],"improve":[180,262],"systems.":[187],"rationale":[189],"our":[191,244],"assume":[196],"every":[197],"\u201cbest\u201d":[201,208,241],"certain":[204],"scenarios,":[205],"each":[211],"may":[213],"be":[214],"different.":[215],"Then":[216],"design":[218],"an":[219],"find":[222],"best":[224],"suggest":[227],"them":[228],"use":[230,239],"it.":[231],"Evaluation":[232],"results":[233],"show":[234],"if":[236],"users":[238],"suggests,":[246],"EER":[248],"system":[251,269],"decreases":[252],"up":[253],"60%.":[255],"This":[256],"means":[257],"proposed":[259],"can":[261],"at":[270],"level":[273],"without":[274],"change":[276],"algorithm.":[279]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
