{"id":"https://openalex.org/W2887614899","doi":"https://doi.org/10.1145/3232116.3232134","title":"Image Enhancement Based on Fourier Transform for Face Recognition with Single Training Sample","display_name":"Image Enhancement Based on Fourier Transform for Face Recognition with Single Training Sample","publication_year":2018,"publication_date":"2018-05-19","ids":{"openalex":"https://openalex.org/W2887614899","doi":"https://doi.org/10.1145/3232116.3232134","mag":"2887614899"},"language":"en","primary_location":{"id":"doi:10.1145/3232116.3232134","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3232116.3232134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Intelligent Information 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/A5006112671","display_name":"Jiazhong He","orcid":null},"institutions":[{"id":"https://openalex.org/I3130751423","display_name":"Shaoguan University","ror":"https://ror.org/0286g6711","country_code":"CN","type":"education","lineage":["https://openalex.org/I3130751423"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiazhong He","raw_affiliation_strings":["Shaoguan University, Shaoguan, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shaoguan University, Shaoguan, Guangdong, China","institution_ids":["https://openalex.org/I3130751423"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056063544","display_name":"Di Zhang","orcid":"https://orcid.org/0000-0001-7135-9174"},"institutions":[{"id":"https://openalex.org/I176834541","display_name":"Guangdong Medical College","ror":"https://ror.org/04k5rxe29","country_code":"CN","type":"education","lineage":["https://openalex.org/I176834541"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Zhang","raw_affiliation_strings":["Guangdong Medical University, Dongguan, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Medical University, Dongguan, Guangdong, China","institution_ids":["https://openalex.org/I176834541"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102338689","display_name":"Yingbiao Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I3130751423","display_name":"Shaoguan University","ror":"https://ror.org/0286g6711","country_code":"CN","type":"education","lineage":["https://openalex.org/I3130751423"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingbiao Jia","raw_affiliation_strings":["Shaoguan University, Shaoguan, Guangdong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shaoguan University, Shaoguan, Guangdong, China","institution_ids":["https://openalex.org/I3130751423"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07984636,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"107","last_page":"111"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9904999732971191,"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/T11448","display_name":"Face recognition and analysis","score":0.9901999831199646,"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/facial-recognition-system","display_name":"Facial recognition system","score":0.7539917230606079},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7402291893959045},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7307125329971313},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6990540027618408},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6426019668579102},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.54647296667099},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.5121254920959473},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46967536211013794},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42796188592910767},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3818112015724182},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23704653978347778}],"concepts":[{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.7539917230606079},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7402291893959045},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7307125329971313},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6990540027618408},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6426019668579102},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.54647296667099},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.5121254920959473},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46967536211013794},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42796188592910767},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3818112015724182},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23704653978347778},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","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},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3232116.3232134","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3232116.3232134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Intelligent Information Processing","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":15,"referenced_works":["https://openalex.org/W1977070767","https://openalex.org/W1983793001","https://openalex.org/W1989702938","https://openalex.org/W2012352340","https://openalex.org/W2017058210","https://openalex.org/W2040277151","https://openalex.org/W2065275771","https://openalex.org/W2070343473","https://openalex.org/W2095189186","https://openalex.org/W2107369107","https://openalex.org/W2113341759","https://openalex.org/W2131273085","https://openalex.org/W2140398892","https://openalex.org/W2155190225","https://openalex.org/W2773992603"],"related_works":["https://openalex.org/W1185300216","https://openalex.org/W3147584709","https://openalex.org/W2977677679","https://openalex.org/W1992327129","https://openalex.org/W2954163146","https://openalex.org/W2381986121","https://openalex.org/W2370918718","https://openalex.org/W2256933480","https://openalex.org/W2132337154","https://openalex.org/W2384651879"],"abstract_inverted_index":{"Face":[0],"recognition":[1,69,115],"with":[2,49],"single":[3,37],"training":[4,17,38,45],"sample":[5,18,46,112],"is":[6,12,47,70,77,94],"a":[7,55,73],"challenging":[8],"problem":[9],"since":[10],"there":[11],"very":[13],"limited":[14],"information":[15,34],"from":[16,79],"set":[19,89],"to":[20,30],"predict":[21],"the":[22,32,36,66,82,86,91],"facial":[23],"variations":[24],"of":[25,35,65,81,85,111],"test":[26],"sample.":[27,67],"In":[28],"order":[29],"enhance":[31],"classification":[33],"sample,":[39],"in":[40],"this":[41],"paper,":[42],"each":[43],"original":[44],"combined":[48],"its":[50],"reconstructed":[51],"image":[52,84],"using":[53],"only":[54],"few":[56],"dominant":[57],"low-frequency":[58],"Fourier":[59],"coefficients":[60],"into":[61],"an":[62],"enhanced":[63,87],"version":[64],"The":[68],"performed":[71],"on":[72,102],"uniform":[74],"eigen-space":[75],"that":[76,107],"obtained":[78],"SVD":[80],"mean":[83],"samples":[88],"and":[90],"coefficient":[92],"matrix":[93],"used":[95],"as":[96,117,119],"feature":[97],"for":[98],"recognition.":[99],"Experimental":[100],"results":[101],"ORL":[103],"face":[104],"database":[105],"show":[106],"our":[108],"proposed":[109],"method":[110],"enhancement":[113],"improves":[114],"accuracy":[116],"well":[118],"speed.":[120]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
