{"id":"https://openalex.org/W2011151058","doi":"https://doi.org/10.1109/icip.2013.6738572","title":"Face recognition using Histogram of co-occurrence Gabor phase patterns","display_name":"Face recognition using Histogram of co-occurrence Gabor phase patterns","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W2011151058","doi":"https://doi.org/10.1109/icip.2013.6738572","mag":"2011151058"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2013.6738572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738572","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100390494","display_name":"Cong Wang","orcid":"https://orcid.org/0000-0002-6068-0103"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Wang","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing (CRIPAC), National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA)","Center for Res. on Intell. Perception & Comput. (CRIPAC), Inst. of Autom., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing (CRIPAC), National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA)","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Center for Res. on Intell. Perception & Comput. (CRIPAC), Inst. of Autom., Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101886040","display_name":"Zhenhua Chai","orcid":"https://orcid.org/0000-0003-1979-1167"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Chai","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing (CRIPAC), National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA)","Center for Res. on Intell. Perception & Comput. (CRIPAC), Inst. of Autom., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing (CRIPAC), National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA)","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Center for Res. on Intell. Perception & Comput. (CRIPAC), Inst. of Autom., Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055505703","display_name":"Zhenan Sun","orcid":"https://orcid.org/0000-0003-4029-9935"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenan Sun","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing (CRIPAC), National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA)","Center for Res. on Intell. Perception & Comput. (CRIPAC), Inst. of Autom., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing (CRIPAC), National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA)","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Center for Res. on Intell. Perception & Comput. (CRIPAC), Inst. of Autom., Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2079,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.42617714,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2777","last_page":"2781"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"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":0.9997000098228455,"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/T10828","display_name":"Biometric Identification and Security","score":0.9927999973297119,"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/T11448","display_name":"Face recognition and analysis","score":0.9919000267982483,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.8261162638664246},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.8088661432266235},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.779415488243103},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.659142255783081},{"id":"https://openalex.org/keywords/gabor-wavelet","display_name":"Gabor wavelet","score":0.6269083023071289},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6105849742889404},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5454845428466797},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5445696115493774},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.49676376581192017},{"id":"https://openalex.org/keywords/phase-congruency","display_name":"Phase congruency","score":0.43018850684165955},{"id":"https://openalex.org/keywords/gabor-transform","display_name":"Gabor transform","score":0.4264410138130188},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3790780007839203},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36328792572021484},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3504665493965149},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.15307900309562683},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11399403214454651},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.05582842230796814}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.8261162638664246},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.8088661432266235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.779415488243103},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.659142255783081},{"id":"https://openalex.org/C136902061","wikidata":"https://www.wikidata.org/wiki/Q16981559","display_name":"Gabor wavelet","level":5,"score":0.6269083023071289},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6105849742889404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5454845428466797},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5445696115493774},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.49676376581192017},{"id":"https://openalex.org/C2777316791","wikidata":"https://www.wikidata.org/wiki/Q17105246","display_name":"Phase congruency","level":3,"score":0.43018850684165955},{"id":"https://openalex.org/C173149727","wikidata":"https://www.wikidata.org/wiki/Q996397","display_name":"Gabor transform","level":4,"score":0.4264410138130188},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3790780007839203},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36328792572021484},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3504665493965149},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.15307900309562683},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11399403214454651},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.05582842230796814},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.0},{"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/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"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/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2013.6738572","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738572","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1545641654","https://openalex.org/W1591385104","https://openalex.org/W1989702938","https://openalex.org/W2033419168","https://openalex.org/W2044465660","https://openalex.org/W2054891869","https://openalex.org/W2075772568","https://openalex.org/W2101193969","https://openalex.org/W2117072267","https://openalex.org/W2118774738","https://openalex.org/W2120954940","https://openalex.org/W2121647436","https://openalex.org/W2131081720","https://openalex.org/W2138451337","https://openalex.org/W2143837352","https://openalex.org/W2146474141","https://openalex.org/W2158424441","https://openalex.org/W2165731615","https://openalex.org/W2180187800","https://openalex.org/W2994340921","https://openalex.org/W3148981562","https://openalex.org/W4205392983","https://openalex.org/W4293768955","https://openalex.org/W6632636493","https://openalex.org/W6635552349","https://openalex.org/W6677495702"],"related_works":["https://openalex.org/W2104492225","https://openalex.org/W1990254706","https://openalex.org/W2404514746","https://openalex.org/W1843372508","https://openalex.org/W2359662965","https://openalex.org/W2130331495","https://openalex.org/W1905998934","https://openalex.org/W2347950327","https://openalex.org/W2357890245","https://openalex.org/W2372614019"],"abstract_inverted_index":{"The":[0],"fusion":[1],"of":[2,17,33,85,102,126,159,170],"Local":[3,39],"Binary":[4],"Patterns":[5,36,42,106],"(LBP)":[6],"and":[7,38,48,116,152],"Gabor":[8,27,34,40,52,61,71,86,104,110,128],"magnitude":[9,53],"features":[10,30,88,112],"has":[11],"been":[12],"demonstrated":[13],"to":[14,51],"be":[15],"one":[16],"the":[18,66,83,124,140,156,160,164],"most":[19],"successful":[20],"descriptors":[21],"for":[22,89,145],"face":[23,91,133],"recognition.":[24],"Recently,":[25],"several":[26],"phase":[28,62,87,129],"based":[29,54,63],"like":[31],"Histogram":[32,101],"Phase":[35,105,111],"(HGPP)":[37],"XOR":[41],"(LGXP)":[43],"also":[44],"show":[45,155],"competitive":[46],"results":[47,149],"complementary":[49],"attributes":[50],"features.":[55],"However,":[56],"in":[57,131,168],"these":[58],"two":[59],"typical":[60],"approaches":[64],"only":[65],"binary":[67],"relationship":[68],"between":[69],"neighboring":[70],"phases":[72],"is":[73],"used,":[74],"which":[75],"may":[76],"lose":[77],"some":[78],"discriminative":[79],"information.":[80],"To":[81],"investigate":[82],"potential":[84],"robust":[90],"recognition,":[92],"this":[93],"paper":[94],"proposes":[95],"a":[96,136],"novel":[97],"local":[98],"descriptor,":[99],"named":[100],"Co-occurrence":[103],"(HCGPP).":[107],"In":[108],"HCGPP,":[109],"are":[113],"first":[114],"extracted":[115],"quantized":[117],"into":[118],"different":[119],"ranges.":[120],"Second":[121],"we":[122],"estimate":[123],"histograms":[125],"cooccurrence":[127],"patterns":[130],"each":[132],"region.":[134],"Finally,":[135],"nearest-neighbor":[137],"classifier":[138],"with":[139],"dissimilarity":[141],"measure":[142],"\u03c72is":[143],"used":[144],"classification.":[146],"Extensive":[147],"experimental":[148],"on":[150],"FERET":[151],"AR":[153],"databases":[154],"significant":[157],"advantages":[158],"proposed":[161],"method":[162],"over":[163],"state-of-the":[165],"art":[166],"ones":[167],"terms":[169],"recognition":[171],"rate.":[172]},"counts_by_year":[{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}