{"id":"https://openalex.org/W2115491658","doi":"https://doi.org/10.1109/itcc.2004.1286620","title":"Face detection technique based on rotation invariant wavelet features","display_name":"Face detection technique based on rotation invariant wavelet features","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W2115491658","doi":"https://doi.org/10.1109/itcc.2004.1286620","mag":"2115491658"},"language":"en","primary_location":{"id":"doi:10.1109/itcc.2004.1286620","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itcc.2004.1286620","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004.","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/A5009498856","display_name":"Satyanadh Gundimada","orcid":null},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Satyanadh Gundimada","raw_affiliation_strings":["VLSI Systems Laboratory, Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA, USA","[Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VLSI Systems Laboratory, Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA, USA","institution_ids":["https://openalex.org/I81365321"]},{"raw_affiliation_string":"[Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA]","institution_ids":["https://openalex.org/I81365321"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061050831","display_name":"Vijayan K. Asari","orcid":"https://orcid.org/0000-0002-3751-5492"},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vijayan Asari","raw_affiliation_strings":["VLSI Systems Laboratory, Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA, USA","[Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VLSI Systems Laboratory, Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA, USA","institution_ids":["https://openalex.org/I81365321"]},{"raw_affiliation_string":"[Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA, USA]","institution_ids":["https://openalex.org/I81365321"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I81365321"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"157","last_page":"158 Vol.2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9975000023841858,"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":0.9975000023841858,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9783999919891357,"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":0.9776999950408936,"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":0.7959873676300049},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6547071933746338},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6410081386566162},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.6375391483306885},{"id":"https://openalex.org/keywords/luminance","display_name":"Luminance","score":0.628669261932373},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.616478443145752},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.6038718223571777},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5975732207298279},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.5973362922668457},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5310360193252563},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.452651709318161},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.449540376663208},{"id":"https://openalex.org/keywords/object-class-detection","display_name":"Object-class detection","score":0.42006099224090576},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33426129817962646}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7959873676300049},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6547071933746338},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6410081386566162},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.6375391483306885},{"id":"https://openalex.org/C73313986","wikidata":"https://www.wikidata.org/wiki/Q355386","display_name":"Luminance","level":2,"score":0.628669261932373},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.616478443145752},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.6038718223571777},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5975732207298279},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.5973362922668457},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5310360193252563},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.452651709318161},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.449540376663208},{"id":"https://openalex.org/C71681937","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object-class detection","level":5,"score":0.42006099224090576},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33426129817962646},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/itcc.2004.1286620","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itcc.2004.1286620","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004.","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.115.9864","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.115.9864","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://csdl.computer.org/comp/proceedings/itcc/2004/2108/02/210820157.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1973975575","https://openalex.org/W2121601095","https://openalex.org/W2147730744","https://openalex.org/W2153493250","https://openalex.org/W6681676112"],"related_works":["https://openalex.org/W2181570714","https://openalex.org/W1581632702","https://openalex.org/W3033332270","https://openalex.org/W212313038","https://openalex.org/W2336272890","https://openalex.org/W3211418293","https://openalex.org/W325114128","https://openalex.org/W4308999381","https://openalex.org/W4308999963","https://openalex.org/W4285815683"],"abstract_inverted_index":{"A":[0,66],"rotation":[1],"and":[2,54,81,95,114,125,141],"scale":[3,67],"invariant":[4,57,68],"face":[5,15,84,153],"detection":[6,98,131,154],"algorithm":[7],"based":[8,104],"on":[9,23],"the":[10,24,29,46,63,72,78,82,90,116,120,157],"texture":[11],"of":[12,75,77,139,156],"a":[13,101,149],"human":[14],"is":[16,21,32,41,86,109,134,160],"proposed.":[17],"Wavelet":[18],"packet":[19,36],"analysis":[20],"performed":[22],"test":[25],"image":[26,85],"to":[27,44,88,162],"get":[28,45],"coefficients.":[30,65],"It":[31],"observed":[33],"that":[34],"wavelet":[35,64],"decomposition":[37],"until":[38],"third":[39],"level":[40],"sufficient":[42],"enough":[43],"necessary":[47],"frequencial":[48],"components":[49],"essential":[50],"for":[51],"classifying":[52],"faces":[53,80,92,94,147],"nonfaces.":[55,96],"Rotation":[56],"textural":[58],"features":[59],"are":[60],"extracted":[61],"from":[62],"distance":[69],"measure":[70],"between":[71],"feature":[73],"vectors":[74],"each":[76],"candidate":[79,91],"prototype":[83],"proposed":[87,133,158],"classify":[89],"into":[93,119],"The":[97,129,152],"process":[99,132],"implements":[100],"nonlinear":[102],"luminance":[103],"lighting":[105,127],"compensation":[106],"method,":[107],"which":[108],"very":[110],"efficient":[111,136],"in":[112,123,137,143,148],"enhancing":[113],"restoring":[115],"natural":[117],"colors":[118],"images":[121],"taken":[122],"darker":[124],"varying":[126],"environments.":[128],"novel":[130],"highly":[135],"terms":[138],"speed":[140],"accuracy":[142],"detecting":[144],"frontal":[145],"view":[146],"complex":[150],"background.":[151],"performance":[155],"system":[159],"comparable":[161],"other":[163],"reported":[164],"leading":[165],"systems.":[166]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}