{"id":"https://openalex.org/W193275998","doi":null,"title":"Indexing Iris Database Using Multi-Dimensional R-Trees","display_name":"Indexing Iris Database Using Multi-Dimensional R-Trees","publication_year":2012,"publication_date":"2012-05-14","ids":{"openalex":"https://openalex.org/W193275998","mag":"193275998"},"language":"en","primary_location":{"id":"mag:193275998","doi":null,"is_oa":false,"landing_page_url":"http://ethesis.nitrkl.ac.in/3505/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"paratext","is_traditional":false,"indexed_in":[],"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/A5074562340","display_name":"Tithy Sahu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tithy Sahu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5074562340"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":true,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9535999894142151,"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":0.9535999894142151,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.027300000190734863,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.013299999758601189,"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":0.8970000147819519},{"id":"https://openalex.org/keywords/r-tree","display_name":"R-tree","score":0.8610000014305115},{"id":"https://openalex.org/keywords/multidimensional-indexing","display_name":"multidimensional indexing","score":0.8130000233650208},{"id":"https://openalex.org/keywords/sift-keypoints","display_name":"SIFT keypoints","score":0.7200000286102295},{"id":"https://openalex.org/keywords/candidate-retrieval","display_name":"candidate retrieval","score":0.5289999842643738}],"concepts":[{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.8448846340179443},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.721082329750061},{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.685502827167511},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6414694786071777},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.5445473790168762},{"id":"https://openalex.org/C59276292","wikidata":"https://www.wikidata.org/wiki/Q580427","display_name":"Database index","level":3,"score":0.5214849710464478},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4787032902240753},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46715015172958374},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.4492258131504059},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44648459553718567},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.4356532096862793},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4304613471031189}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:193275998","doi":null,"is_oa":false,"landing_page_url":"http://ethesis.nitrkl.ac.in/3505/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1845229441","https://openalex.org/W1963500575","https://openalex.org/W1998890624","https://openalex.org/W1998991383","https://openalex.org/W2030827865","https://openalex.org/W2034822756","https://openalex.org/W2119605622","https://openalex.org/W2127865654","https://openalex.org/W2133995247","https://openalex.org/W2140959843","https://openalex.org/W2142299222","https://openalex.org/W2147948670","https://openalex.org/W2151103935","https://openalex.org/W2154367286","https://openalex.org/W2157592049","https://openalex.org/W2538632371"],"related_works":["https://openalex.org/W320871059","https://openalex.org/W1998890624","https://openalex.org/W2801657562","https://openalex.org/W2738308647","https://openalex.org/W2052462474","https://openalex.org/W4206741040","https://openalex.org/W2185237962","https://openalex.org/W9938492","https://openalex.org/W2265538924","https://openalex.org/W1971697504"],"abstract_inverted_index":{"Iris":[0],"is":[1,40,52,82,86,105,147],"one":[2],"of":[3,28,37,61,67,70,139],"the":[4,26,35,65,80],"most":[5],"widely":[6],"used":[7,128],"biometric":[8,39],"modality":[9],"for":[10,132,141],"recognition":[11],"due":[12],"to":[13,32,54,74,88,118,129],"its":[14],"reliability,":[15],"non-invasive":[16],"characteristic,":[17],"speed":[18],"and":[19,56,91,122,153],"performance.":[20],"The":[21,145],"patterns":[22],"remain":[23],"stable":[24],"throughout":[25],"lifetime":[27],"an":[29,98,137],"individual.":[30],"Attributable":[31],"these":[33],"advantages,":[34],"application":[36,138],"iris":[38,68,142],"increasingly":[41],"encouraged":[42],"by":[43],"various":[44],"commercial":[45],"as":[46,48],"well":[47],"government":[49],"agencies.":[50],"Indexing":[51],"done":[53],"identify":[55],"retrieve":[57],"a":[58,76],"small":[59],"subset":[60],"candidate":[62],"data":[63,69],"from":[64],"database":[66,81,143],"individuals":[71],"in":[72],"order":[73],"determine":[75],"possible":[77],"match.":[78],"Since":[79],"extremely":[83],"large,":[84],"it":[85],"necessary":[87],"find":[89],"fast":[90],"efficient":[92,99],"indexing":[93,103],"methods.":[94],"In":[95],"this":[96],"thesis,":[97],"local":[100],"feature":[101,111],"based":[102],"approach":[104],"proposed":[106],"using":[107,149],"clustered":[108],"scale":[109],"invariant":[110],"transform":[112],"(SIFT)":[113],"keypoints,":[114],"that":[115],"achieves":[116],"invariance":[117],"similarity":[119],"transformations,":[120],"illumination":[121],"occlusion.":[123],"These":[124],"cluster":[125],"centers":[126],"are":[127],"construct":[130],"R-trees":[131,140],"indexing.":[133,144],"This":[134],"thesis":[135],"proposes":[136],"system":[146],"tested":[148],"publicly":[150],"available":[151],"BATH":[152],"CASIA-IrisV4":[154],"databases.":[155]},"counts_by_year":[],"updated_date":"2026-07-14T23:32:53.992493","created_date":"2016-06-24T00:00:00"}
