{"id":"https://openalex.org/W2243629480","doi":"https://doi.org/10.1109/dicta.2015.7371261","title":"Face Recognition Using Two-Dimensional Tunable-Q Wavelet Transform","display_name":"Face Recognition Using Two-Dimensional Tunable-Q Wavelet Transform","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2243629480","doi":"https://doi.org/10.1109/dicta.2015.7371261","mag":"2243629480"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2015.7371261","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2015.7371261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","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/A5109852774","display_name":"T. Sunil Kumar","orcid":null},"institutions":[{"id":"https://openalex.org/I64295750","display_name":"Indian Institute of Technology Indore","ror":"https://ror.org/01hhf7w52","country_code":"IN","type":"education","lineage":["https://openalex.org/I64295750"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"T. Sunil Kumar","raw_affiliation_strings":["Electrical Engineering, Indian Institute of Technology Indore, Indore, India"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering, Indian Institute of Technology Indore, Indore, India","institution_ids":["https://openalex.org/I64295750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016019632","display_name":"Vivek Kanhangad","orcid":"https://orcid.org/0000-0002-9791-3695"},"institutions":[{"id":"https://openalex.org/I64295750","display_name":"Indian Institute of Technology Indore","ror":"https://ror.org/01hhf7w52","country_code":"IN","type":"education","lineage":["https://openalex.org/I64295750"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vivek Kanhangad","raw_affiliation_strings":["Electrical Engineering, Indian Institute of Technology Indore, Indore, India"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering, Indian Institute of Technology Indore, Indore, India","institution_ids":["https://openalex.org/I64295750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5109852774"],"corresponding_institution_ids":["https://openalex.org/I64295750"],"apc_list":null,"apc_paid":null,"fwci":0.1841,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59786942,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"8","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9948999881744385,"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":0.9948999881744385,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9891999959945679,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9814000129699707,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7149204611778259},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.7077080011367798},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7031106948852539},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6551847457885742},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6434940099716187},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6200234889984131},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5935713052749634},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5861152410507202},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5268182754516602},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4464942514896393},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3810182809829712},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24216538667678833}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7149204611778259},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.7077080011367798},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7031106948852539},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6551847457885742},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6434940099716187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6200234889984131},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5935713052749634},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5861152410507202},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5268182754516602},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4464942514896393},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3810182809829712},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24216538667678833},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dicta.2015.7371261","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2015.7371261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","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":26,"referenced_works":["https://openalex.org/W21245430","https://openalex.org/W590134283","https://openalex.org/W1527836117","https://openalex.org/W1977731970","https://openalex.org/W1989702938","https://openalex.org/W2080462706","https://openalex.org/W2101789093","https://openalex.org/W2103560185","https://openalex.org/W2111415681","https://openalex.org/W2112797878","https://openalex.org/W2121647436","https://openalex.org/W2127300676","https://openalex.org/W2132672282","https://openalex.org/W2146076056","https://openalex.org/W2146143569","https://openalex.org/W2158275940","https://openalex.org/W2163352848","https://openalex.org/W2167049709","https://openalex.org/W2799061466","https://openalex.org/W2799244375","https://openalex.org/W6600847314","https://openalex.org/W6617464125","https://openalex.org/W6675717848","https://openalex.org/W6675783759","https://openalex.org/W6678812539","https://openalex.org/W7014191107"],"related_works":["https://openalex.org/W2382174632","https://openalex.org/W2129959498","https://openalex.org/W2107628111","https://openalex.org/W2784060934","https://openalex.org/W2394004323","https://openalex.org/W2902714807","https://openalex.org/W2537489131","https://openalex.org/W2394084632","https://openalex.org/W2077021924","https://openalex.org/W2985118265"],"abstract_inverted_index":{"Tunable-Q":[0],"wavelet":[1,7,30],"transform":[2,8,31],"(TQWT)":[3],"is":[4,58,75,115],"a":[5,25,50],"discrete":[6],"that":[9,125],"has":[10],"been":[11],"very":[12],"effective":[13],"in":[14,136],"decomposing":[15],"signals":[16],"with":[17,118],"oscillatory":[18],"nature.":[19],"In":[20,83],"this":[21],"paper,":[22],"we":[23],"develop":[24],"new":[26],"two":[27,102],"dimensional":[28],"tunable-Q":[29],"(2D-TQWT)":[32],"using":[33,44],"its":[34],"1D":[35],"prototype":[36],"and":[37,106],"propose":[38],"an":[39],"approach":[40,48,114],"for":[41,139],"face":[42,51,94,108],"recognition":[43,95,130],"2D-TQWT.":[45],"The":[46,110],"proposed":[47,91,113],"decomposes":[49],"image":[52],"into":[53],"four":[54],"sub":[55],"bands.":[56],"This":[57,72],"followed":[59],"by":[60],"extraction":[61],"of":[62,89,112],"local":[63],"binary":[64],"pattern":[65],"based":[66,93],"histogram":[67],"features":[68],"from":[69],"different":[70],"sub-bands.":[71],"extracted":[73],"information":[74],"further":[76],"combined":[77],"to":[78,85],"get":[79],"the":[80,87,90,126],"final":[81],"representation.":[82],"order":[84],"evaluate":[86],"performance":[88,111],"2D-TQWT":[92,127],"approach,":[96],"experiments":[97,138],"are":[98],"carried":[99],"out":[100],"on":[101],"datasets":[103],"namely,":[104],"Yale":[105],"ORL":[107],"datasets.":[109],"also":[116],"compared":[117],"other":[119,133],"existing":[120],"wavelets.":[121],"Experimental":[122],"results":[123],"show":[124],"yields":[128],"better":[129],"accuracy":[131],"than":[132],"wavelets":[134],"employed":[135],"our":[137],"comparison.":[140]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}