{"id":"https://openalex.org/W4244757147","doi":"https://doi.org/10.1109/icpr.2004.1334108","title":"Gabor wavelets and kernel direct discriminant analysis for face recognition","display_name":"Gabor wavelets and kernel direct discriminant analysis for face recognition","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W4244757147","doi":"https://doi.org/10.1109/icpr.2004.1334108"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2004.1334108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2004.1334108","pdf_url":null,"source":{"id":"https://openalex.org/S4363608750","display_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","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/A5019313200","display_name":"Linlin Shen","orcid":"https://orcid.org/0000-0003-1420-0815"},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"LinLin Shen","raw_affiliation_strings":["School of Computer Science & IT, University of Nottingham, Nottingham, UK"],"affiliations":[{"raw_affiliation_string":"School of Computer Science & IT, University of Nottingham, Nottingham, UK","institution_ids":["https://openalex.org/I142263535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100608938","display_name":"Bai Li","orcid":"https://orcid.org/0000-0002-8966-8992"},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Li Bai","raw_affiliation_strings":["School of Computer Science & IT, University of Nottingham, Nottingham, UK"],"affiliations":[{"raw_affiliation_string":"School of Computer Science & IT, University of Nottingham, Nottingham, UK","institution_ids":["https://openalex.org/I142263535"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5019313200"],"corresponding_institution_ids":["https://openalex.org/I142263535"],"apc_list":null,"apc_paid":null,"fwci":3.0429,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.92354911,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"284","last_page":"287 Vol.1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994000196456909,"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":0.9994000196456909,"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/T13579","display_name":"Image and Video Stabilization","score":0.9664000272750854,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9628000259399414,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.850857138633728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8317734003067017},{"id":"https://openalex.org/keywords/gabor-wavelet","display_name":"Gabor wavelet","score":0.719290018081665},{"id":"https://openalex.org/keywords/kernel-fisher-discriminant-analysis","display_name":"Kernel Fisher discriminant analysis","score":0.6654572486877441},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.6629699468612671},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.64406418800354},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6036592125892639},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5869721174240112},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5408045053482056},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5167802572250366},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.502263069152832},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.45020830631256104},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.42844194173812866},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4252896010875702},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4248999059200287},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4153267443180084},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39963728189468384},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.33587801456451416},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.32379674911499023},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.3031754493713379},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.22806581854820251},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.19993320107460022}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.850857138633728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8317734003067017},{"id":"https://openalex.org/C136902061","wikidata":"https://www.wikidata.org/wiki/Q16981559","display_name":"Gabor wavelet","level":5,"score":0.719290018081665},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.6654572486877441},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.6629699468612671},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.64406418800354},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6036592125892639},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5869721174240112},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5408045053482056},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5167802572250366},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.502263069152832},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.45020830631256104},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.42844194173812866},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4252896010875702},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4248999059200287},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4153267443180084},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39963728189468384},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.33587801456451416},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.32379674911499023},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3031754493713379},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.22806581854820251},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.19993320107460022},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2004.1334108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2004.1334108","pdf_url":null,"source":{"id":"https://openalex.org/S4363608750","display_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1031167700","https://openalex.org/W1985809919","https://openalex.org/W2021012145","https://openalex.org/W2028325389","https://openalex.org/W2041657594","https://openalex.org/W2095757522","https://openalex.org/W2104163856","https://openalex.org/W2113341759","https://openalex.org/W2120954940","https://openalex.org/W2121647436","https://openalex.org/W2135188079","https://openalex.org/W2138451337","https://openalex.org/W2143304877","https://openalex.org/W2165731615"],"related_works":["https://openalex.org/W2905418897","https://openalex.org/W1607829095","https://openalex.org/W3033319502","https://openalex.org/W1982817239","https://openalex.org/W3093470103","https://openalex.org/W2046363782","https://openalex.org/W2375053148","https://openalex.org/W1967057085","https://openalex.org/W1980862902","https://openalex.org/W1995477328"],"abstract_inverted_index":{"A":[0,57,116],"novel":[1,124],"Gabor-Kernel":[2],"face":[3,15,62,67],"recognition":[4],"method":[5,128],"is":[6,41,69],"proposed":[7],"in":[8],"this":[9],"paper.":[10],"This":[11],"involves":[12],"convolving":[13],"a":[14,18,134,144],"image":[16],"with":[17],"series":[19],"of":[20,59,80,112],"Gabor":[21,34,108,125],"wavelets":[22],"at":[23],"different":[24],"scales,":[25],"locations,":[26],"and":[27,29,93,148],"orientations":[28],"extracting":[30],"features":[31,104],"from":[32,64,107],"resulting":[33],"filtered":[35,109],"images.":[36,115],"kernel":[37,88],"discriminant":[38,95],"analysis":[39,91,96],"(KDDA)":[40],"then":[42],"applied":[43],"to":[44,71],"the":[45,65,73,78,113,123,130],"feature":[46],"vectors":[47],"for":[48,122],"dimension":[49],"reduction":[50],"as":[51,53,87],"well":[52],"class":[54],"separability":[55],"enhancement.":[56],"database":[58,68,132],"600":[60],"frontal-view":[61],"images":[63,110],"FERET":[66,131],"used":[70],"test":[72],"method.":[74],"Experimental":[75],"results":[76],"demonstrate":[77],"advantage":[79],"KDDA":[81,127],"over":[82],"other":[83],"Kernel":[84],"methods":[85],"such":[86],"principal":[89],"component":[90],"(KPCA)":[92],"general":[94],"(GDA).":[97],"Significant":[98],"improvements":[99],"are":[100,105],"also":[101],"observed":[102,121],"when":[103],"extracted":[106],"instead":[111],"original":[114],"94%":[117],"accuracy":[118],"has":[119],"been":[120],"+":[126],"on":[129],"using":[133],"simple":[135],"classifier,":[136],"which":[137],"could":[138],"be":[139],"further":[140],"improved":[141],"by":[142],"employing":[143],"more":[145],"complex":[146],"classifier":[147],"distance":[149],"measurer.":[150]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}