{"id":"https://openalex.org/W2563660710","doi":"https://doi.org/10.1109/uemcon.2016.7777823","title":"Employing vector quantization in a transform domain for face recognition","display_name":"Employing vector quantization in a transform domain for face recognition","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2563660710","doi":"https://doi.org/10.1109/uemcon.2016.7777823","mag":"2563660710"},"language":"en","primary_location":{"id":"doi:10.1109/uemcon.2016.7777823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/uemcon.2016.7777823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 7th Annual Ubiquitous Computing, Electronics &amp; Mobile Communication Conference (UEMCON)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://stars.library.ucf.edu/scopus2015/3964","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023854535","display_name":"Taif Alobaidi","orcid":"https://orcid.org/0000-0003-3151-164X"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Taif Alobaidi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100756343","display_name":"Ahmed Aldhahab","orcid":"https://orcid.org/0000-0002-1935-1332"},"institutions":[{"id":"https://openalex.org/I166455938","display_name":"University of Babylon","ror":"https://ror.org/0170edc15","country_code":"IQ","type":"education","lineage":["https://openalex.org/I166455938"]},{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["IQ","US"],"is_corresponding":false,"raw_author_name":"Ahmed Aldhahab","raw_affiliation_strings":["Department of Electrical Engineering, University of Babylon, Babylon, Iraq","Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Babylon, Babylon, Iraq","institution_ids":["https://openalex.org/I166455938"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110204942","display_name":"Wasfy B. Mikhael","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wasfy B. Mikhael","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5023854535"],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":null,"apc_paid":null,"fwci":0.5068,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.74307284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"159","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9980000257492065,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9980000257492065,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9954000115394592,"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":0.9757000207901001,"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/codebook","display_name":"Codebook","score":0.9288592338562012},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.7606726884841919},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.7471281886100769},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6984789371490479},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6489379405975342},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6488534212112427},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6255940198898315},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.5685096383094788},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5360000729560852},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4731494188308716},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4456348419189453},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44198697805404663},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.4242277145385742},{"id":"https://openalex.org/keywords/linde\u2013buzo\u2013gray-algorithm","display_name":"Linde\u2013Buzo\u2013Gray algorithm","score":0.4134008288383484},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35004353523254395}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.9288592338562012},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.7606726884841919},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.7471281886100769},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6984789371490479},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6489379405975342},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6488534212112427},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6255940198898315},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.5685096383094788},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5360000729560852},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4731494188308716},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4456348419189453},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44198697805404663},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.4242277145385742},{"id":"https://openalex.org/C93372532","wikidata":"https://www.wikidata.org/wiki/Q6552455","display_name":"Linde\u2013Buzo\u2013Gray algorithm","level":3,"score":0.4134008288383484},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35004353523254395},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/uemcon.2016.7777823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/uemcon.2016.7777823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 7th Annual Ubiquitous Computing, Electronics &amp; Mobile Communication Conference (UEMCON)","raw_type":"proceedings-article"},{"id":"pmh:oai:stars.library.ucf.edu:scopus2015-4963","is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/scopus2015/3964","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus Export 2015-2019","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:stars.library.ucf.edu:scopus2015-4963","is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/scopus2015/3964","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus Export 2015-2019","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W565449262","https://openalex.org/W1634005169","https://openalex.org/W1680392829","https://openalex.org/W1995664854","https://openalex.org/W1997011019","https://openalex.org/W2033419168","https://openalex.org/W2062322937","https://openalex.org/W2069165391","https://openalex.org/W2110793766","https://openalex.org/W2134383396","https://openalex.org/W2319633682","https://openalex.org/W6637386731"],"related_works":["https://openalex.org/W2352648934","https://openalex.org/W2017514583","https://openalex.org/W2391875658","https://openalex.org/W2100120615","https://openalex.org/W1929869830","https://openalex.org/W2017401491","https://openalex.org/W2387054321","https://openalex.org/W2158612577","https://openalex.org/W2148772884","https://openalex.org/W2084027797"],"abstract_inverted_index":{"A":[0],"face":[1],"recognition":[2,91,148],"system":[3,22,100,136],"using":[4,63,75,103,129],"an":[5],"integration":[6],"of":[7,24],"Discrete":[8],"Cosine":[9],"Transform":[10],"(DCT)":[11],"and":[12,31,111],"Vector":[13],"quantization":[14],"(VQ)":[15],"is":[16,41,54,61,101,137],"proposed":[17,135],"in":[18],"this":[19],"paper.":[20],"The":[21,59,71,84,99,124,134],"consists":[23],"two":[25],"main":[26],"phases,":[27],"namely,":[28,107],"Feature":[29],"Extraction":[30],"Recognition.":[32],"In":[33],"the":[34,37,49,64,80,90,95,141,147],"first":[35],"phase,":[36],"input":[38,81],"facial":[39,82,116,120],"image":[40],"divided":[42],"into":[43],"blocks":[44],"with":[45],"dimensions":[46],"equal":[47],"to":[48,88,139],"codeword":[50],"dimensions.":[51],"Then,":[52],"DCT":[53],"applied":[55],"on":[56,94],"each":[57],"block.":[58],"codebook":[60],"initialized":[62],"Kekre":[65],"Fast":[66],"Codebook":[67,73],"Generation":[68],"(KFCG)":[69],"method.":[70],"Final":[72],"computed":[74],"VQ":[76],"algorithm":[77],"efficiently":[78],"represents":[79],"image.":[83],"second":[85],"phase":[86],"aims":[87],"find":[89],"rates":[92],"based":[93],"Euclidean":[96],"distance":[97],"criterion.":[98],"evaluated":[102],"four":[104],"different":[105,115],"databases,":[106],"ORL,":[108],"YALE,":[109],"FERET,":[110],"FEI":[112],"that":[113],"have":[114],"variations,":[117],"such":[118],"as":[119,144,146],"expressions,":[121],"illuminations,":[122],"etc.":[123],"experimental":[125],"results":[126],"are":[127],"analyzed":[128],"K-fold":[130],"Cross":[131],"Validation":[132],"(CV).":[133],"shown":[138],"improve":[140],"storage":[142],"requirements,":[143],"well":[145],"rates.":[149]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
