{"id":"https://openalex.org/W1514862419","doi":"https://doi.org/10.1109/fcv.2015.7103754","title":"Phonographic image recognition using fusion of scale invariant descriptor","display_name":"Phonographic image recognition using fusion of scale invariant descriptor","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W1514862419","doi":"https://doi.org/10.1109/fcv.2015.7103754","mag":"1514862419"},"language":"en","primary_location":{"id":"doi:10.1109/fcv.2015.7103754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fcv.2015.7103754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV)","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/A5080634966","display_name":"I Gede Pasek Suta Wijaya","orcid":"https://orcid.org/0000-0002-3813-013X"},"institutions":[{"id":"https://openalex.org/I168180000","display_name":"University of Mataram","ror":"https://ror.org/00fq07k50","country_code":"ID","type":"education","lineage":["https://openalex.org/I168180000"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"I Gede Pasek Suta Wijaya","raw_affiliation_strings":["Universitas Mataram, Mataram, Nusa Tenggara Barat, ID","Informatics Engineering Dept., Engineering Faculty, Mataram University, Mataram Lombok, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Mataram, Mataram, Nusa Tenggara Barat, ID","institution_ids":["https://openalex.org/I168180000"]},{"raw_affiliation_string":"Informatics Engineering Dept., Engineering Faculty, Mataram University, Mataram Lombok, Indonesia","institution_ids":["https://openalex.org/I168180000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007413198","display_name":"Ida Bagus Ketut Widiartha","orcid":"https://orcid.org/0000-0002-8014-6653"},"institutions":[{"id":"https://openalex.org/I168180000","display_name":"University of Mataram","ror":"https://ror.org/00fq07k50","country_code":"ID","type":"education","lineage":["https://openalex.org/I168180000"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"I B K Widiartha","raw_affiliation_strings":["Informatics Engineering Dept., Mataram University Mataram Lombok, Indonesia","Informatics Engineering Dept., Engineering Faculty, Mataram University, Mataram Lombok, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Informatics Engineering Dept., Mataram University Mataram Lombok, Indonesia","institution_ids":["https://openalex.org/I168180000"]},{"raw_affiliation_string":"Informatics Engineering Dept., Engineering Faculty, Mataram University, Mataram Lombok, Indonesia","institution_ids":["https://openalex.org/I168180000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113818116","display_name":"Keiichi Uchimura","orcid":null},"institutions":[{"id":"https://openalex.org/I96036126","display_name":"Kumamoto University","ror":"https://ror.org/02cgss904","country_code":"JP","type":"education","lineage":["https://openalex.org/I96036126"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keiichi Uchimura","raw_affiliation_strings":["Graduate School of Science and Technology, Kumamoto University Kumamoto Shi, Japan","Graduate School of Science and Technology, Kumamoto University , Kumamoto-shi, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Kumamoto University Kumamoto Shi, Japan","institution_ids":["https://openalex.org/I96036126"]},{"raw_affiliation_string":"Graduate School of Science and Technology, Kumamoto University , Kumamoto-shi, Japan","institution_ids":["https://openalex.org/I96036126"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016988662","display_name":"Gou Koutaki","orcid":"https://orcid.org/0000-0002-3414-1085"},"institutions":[{"id":"https://openalex.org/I96036126","display_name":"Kumamoto University","ror":"https://ror.org/02cgss904","country_code":"JP","type":"education","lineage":["https://openalex.org/I96036126"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Gou Koutaki","raw_affiliation_strings":["Graduate School of Science and Technology, Kumamoto University Kumamoto Shi, Japan","Graduate School of Science and Technology, Kumamoto University , Kumamoto-shi, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Kumamoto University Kumamoto Shi, Japan","institution_ids":["https://openalex.org/I96036126"]},{"raw_affiliation_string":"Graduate School of Science and Technology, Kumamoto University , Kumamoto-shi, Japan","institution_ids":["https://openalex.org/I96036126"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5407,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.72627872,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"144","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9951000213623047,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9951000213623047,"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":0.9939000010490417,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9936000108718872,"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/invariant","display_name":"Invariant (physics)","score":0.751050591468811},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7441377639770508},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6583960056304932},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6268621683120728},{"id":"https://openalex.org/keywords/scale-invariance","display_name":"Scale invariance","score":0.6087110638618469},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5520310401916504},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4833957254886627},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.48110049962997437},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.452362984418869},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44067704677581787},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.43120312690734863},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43037179112434387},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4206825792789459},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29166918992996216},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08894866704940796},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06893196702003479}],"concepts":[{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.751050591468811},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7441377639770508},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6583960056304932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6268621683120728},{"id":"https://openalex.org/C135593079","wikidata":"https://www.wikidata.org/wiki/Q1750766","display_name":"Scale invariance","level":2,"score":0.6087110638618469},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5520310401916504},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4833957254886627},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.48110049962997437},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.452362984418869},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44067704677581787},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.43120312690734863},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43037179112434387},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4206825792789459},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29166918992996216},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08894866704940796},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06893196702003479},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","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/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","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:10.1109/fcv.2015.7103754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fcv.2015.7103754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 21st Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","score":0.5600000023841858,"display_name":"Gender equality"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320326473","display_name":"Japan Student Services Organization","ror":"https://ror.org/04bcrs686"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W947857775","https://openalex.org/W1498915505","https://openalex.org/W1634159060","https://openalex.org/W1673002162","https://openalex.org/W1821971621","https://openalex.org/W1971841223","https://openalex.org/W1975188435","https://openalex.org/W2010116109","https://openalex.org/W2051210749","https://openalex.org/W2127744755","https://openalex.org/W2138451337","https://openalex.org/W2151103935","https://openalex.org/W2315214263","https://openalex.org/W2364573303","https://openalex.org/W3196375845","https://openalex.org/W4285719527","https://openalex.org/W6624952431","https://openalex.org/W6636688041","https://openalex.org/W6637398742","https://openalex.org/W6707897595"],"related_works":["https://openalex.org/W1750358731","https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2139242969","https://openalex.org/W2379054866","https://openalex.org/W2549658594","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2350422455"],"abstract_inverted_index":{"The":[0,13,37,84,101,129],"paper":[1],"presents":[2],"a":[3,108],"pornographic":[4,14,65,82,95,112,123,168,196,202],"image":[5,15,18],"recognition":[6,113],"using":[7],"fusion":[8,38,189],"of":[9,24,39,64,75,78,81,94,104,167,179,190,201],"scale":[10,40,61,72,191],"invariant":[11,41,62,73,192],"descriptor.":[12],"means":[16,157],"the":[17,71,91,121,134,158,177,188],"contains":[19],"and":[20,34,60,127,149,153],"shows":[21],"genital":[22],"elements":[23],"human":[25],"body":[26],"having":[27],"large":[28,92],"variability":[29,52,93],"due":[30,97],"to":[31,49,89,98,119,138,163],"poses,":[32],"lighting,":[33],"backgrounds":[35],"variations.":[36,100],"descriptor":[42,74,193],"that":[43,57,133],"is":[44,47,58,67,87,161],"holistic":[45,55,199],"feature":[46,56,200],"employed":[48],"handle":[50,90],"those":[51],"problems.":[53],"This":[54,182],"pose":[59],"information":[63,197],"images":[66,96,124],"extracted":[68],"by":[69,125],"fusing":[70],"skin":[76,85],"region":[77],"interests":[79],"(ROIs)":[80],"images.":[83,169,203],"ROI":[86],"used":[88],"background":[99],"main":[102],"aim":[103],"this":[105],"research":[106],"finds":[107],"good":[109],"solution":[110],"for":[111],"system,":[114],"which":[115],"can":[116,184],"be":[117,185],"developed":[118],"limit":[120],"accessing":[122],"teenagers":[126],"children.":[128],"experimental":[130],"results":[131,183],"show":[132],"proposed":[135,159],"method":[136,160],"tends":[137],"provide":[139],"high":[140],"enough":[141,147],"accuracy":[142],"more":[143],"than":[144,176],"80%,":[145],"small":[146],"FNR":[148],"FPR":[150],"bout":[151],"2.77%":[152],"28.79%,":[154],"respectively.":[155],"It":[156],"suitable":[162],"develop":[164],"rejection":[165],"system":[166],"Furthermore,":[170],"these":[171],"achievements":[172,178],"are":[173],"much":[174],"better":[175],"established":[180],"methods.":[181],"achieved":[186],"because":[187],"consists":[194],"rich":[195],"representing":[198]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
