{"id":"https://openalex.org/W2792082278","doi":"https://doi.org/10.1007/s41095-018-0106-z","title":"Automatic texture exemplar extraction based on global and local textureness measures","display_name":"Automatic texture exemplar extraction based on global and local textureness measures","publication_year":2018,"publication_date":"2018-03-19","ids":{"openalex":"https://openalex.org/W2792082278","doi":"https://doi.org/10.1007/s41095-018-0106-z","mag":"2792082278"},"language":"en","primary_location":{"id":"doi:10.1007/s41095-018-0106-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-018-0106-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0106-z.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0106-z.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026540573","display_name":"Huisi Wu","orcid":"https://orcid.org/0000-0002-0399-9089"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huisi Wu","raw_affiliation_strings":["Shenzhen University, Shenzhen 518000, China","Shenzhen University, Shenzhen, 518000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen 518000, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Shenzhen University, Shenzhen, 518000, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070121305","display_name":"Xiaomeng Lyu","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaomeng Lyu","raw_affiliation_strings":["Shenzhen University, Shenzhen 518000, China","Shenzhen University, Shenzhen, 518000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen 518000, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Shenzhen University, Shenzhen, 518000, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039966518","display_name":"Zhenkun Wen","orcid":"https://orcid.org/0000-0003-2124-9799"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenkun Wen","raw_affiliation_strings":["Shenzhen University, Shenzhen 518000, China","Shenzhen University, Shenzhen, 518000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen 518000, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Shenzhen University, Shenzhen, 518000, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026540573"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":3.3245,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.92478696,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"4","issue":"2","first_page":"173","last_page":"184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9879000186920166,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9865000247955322,"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":0.7571110725402832},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7084070444107056},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.6358992457389832},{"id":"https://openalex.org/keywords/texture-synthesis","display_name":"Texture synthesis","score":0.6192896366119385},{"id":"https://openalex.org/keywords/texture-filtering","display_name":"Texture filtering","score":0.607088029384613},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.5555920600891113},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5465821623802185},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5425293445587158},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.5018348693847656},{"id":"https://openalex.org/keywords/texture-compression","display_name":"Texture compression","score":0.5005254745483398},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4958828389644623},{"id":"https://openalex.org/keywords/texel","display_name":"Texel","score":0.4921206831932068},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4800109267234802},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4326328635215759},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30771952867507935},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24011379480361938},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.21288201212882996},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.116539865732193}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7571110725402832},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7084070444107056},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.6358992457389832},{"id":"https://openalex.org/C50494287","wikidata":"https://www.wikidata.org/wiki/Q658467","display_name":"Texture synthesis","level":5,"score":0.6192896366119385},{"id":"https://openalex.org/C144743038","wikidata":"https://www.wikidata.org/wiki/Q3267765","display_name":"Texture filtering","level":5,"score":0.607088029384613},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.5555920600891113},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5465821623802185},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5425293445587158},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.5018348693847656},{"id":"https://openalex.org/C54243161","wikidata":"https://www.wikidata.org/wiki/Q39333","display_name":"Texture compression","level":5,"score":0.5005254745483398},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4958828389644623},{"id":"https://openalex.org/C167759928","wikidata":"https://www.wikidata.org/wiki/Q2349836","display_name":"Texel","level":2,"score":0.4921206831932068},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4800109267234802},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4326328635215759},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30771952867507935},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24011379480361938},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.21288201212882996},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.116539865732193}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s41095-018-0106-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-018-0106-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0106-z.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0cec76cc4c874b11b2697224c3715a53","is_oa":true,"landing_page_url":"https://doaj.org/article/0cec76cc4c874b11b2697224c3715a53","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computational Visual Media, Vol 4, Iss 2, Pp 173-184 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s41095-018-0106-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-018-0106-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0106-z.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5600000023841858,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G5448901618","display_name":null,"funder_award_id":"61572328","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G765992311","display_name":null,"funder_award_id":"61303101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325571","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70"},{"id":"https://openalex.org/F4320330400","display_name":"Shenzhen Research Foundation","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2792082278.pdf","grobid_xml":"https://content.openalex.org/works/W2792082278.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1566135517","https://openalex.org/W1985201786","https://openalex.org/W1999360130","https://openalex.org/W2011406694","https://openalex.org/W2028500380","https://openalex.org/W2035308043","https://openalex.org/W2041971124","https://openalex.org/W2061987443","https://openalex.org/W2086383433","https://openalex.org/W2093224205","https://openalex.org/W2099594591","https://openalex.org/W2125771762","https://openalex.org/W2127860858","https://openalex.org/W2128598988","https://openalex.org/W2149521538","https://openalex.org/W2151406969","https://openalex.org/W2153635508","https://openalex.org/W2153844133","https://openalex.org/W2161693169","https://openalex.org/W2163352848","https://openalex.org/W2398064218","https://openalex.org/W2614670326","https://openalex.org/W2739140129","https://openalex.org/W2913059114","https://openalex.org/W2964193438","https://openalex.org/W4229971152","https://openalex.org/W4234552385","https://openalex.org/W4242177601","https://openalex.org/W4248430277","https://openalex.org/W4301419656"],"related_works":["https://openalex.org/W2036879703","https://openalex.org/W2166988704","https://openalex.org/W2743128629","https://openalex.org/W49703711","https://openalex.org/W1485582877","https://openalex.org/W2123435361","https://openalex.org/W2348548569","https://openalex.org/W2727263686","https://openalex.org/W2112748650","https://openalex.org/W2028500380"],"abstract_inverted_index":{"Texture":[0],"synthesis":[1,15],"is":[2,41],"widely":[3],"used":[4],"for":[5,46],"modeling":[6],"the":[7,47,75,126,132,142],"appearance":[8],"of":[9,19,29,77,125,135,189,194],"virtual":[10],"objects.":[11],"However,":[12],"traditional":[13],"texture":[14,32,36,62,79,121,167],"techniques":[16],"emphasize":[17],"creation":[18],"optimal":[20,166],"target":[21],"textures,":[22],"and":[23,52,69,89,140,150,160,171,178,207],"pay":[24],"insufficient":[25],"attention":[26],"to":[27,87,106],"choice":[28],"suitable":[30],"input":[31],"exemplars.":[33],"Currently,":[34],"obtaining":[35],"exemplars":[37,122,168],"from":[38,93,110],"natural":[39,95],"images":[40,190],"a":[42,94,103,136,158,187,208],"labor":[43],"intensive":[44],"task":[45],"artists,":[48],"requiring":[49],"careful":[50],"photography":[51],"significant":[53],"postprocessing.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58,81,101,129,164],"present":[59],"an":[60,205],"automatic":[61],"exemplar":[63],"extraction":[64],"method":[65,185],"based":[66],"on":[67,186],"global":[68,98,177],"local":[70,133,143,179],"textureness":[71,99,134,180],"measures.":[72,181],"To":[73,118],"improve":[74],"efficiency":[76],"dominant":[78,127,151],"identification,":[80],"first":[82],"perform":[83],"Poisson":[84],"disk":[85],"sampling":[86],"randomly":[88],"uniformly":[90],"crop":[91],"patches":[92,109,174],"image.":[96],"For":[97],"assessment,":[100],"use":[102],"GIST":[104],"descriptor":[105],"distinguish":[107],"textured":[108],"non-textured":[111],"patches,":[112],"in":[113],"conjunction":[114],"with":[115,191,200],"SVM":[116],"prediction.":[117],"identify":[119],"real":[120],"consisting":[123],"solely":[124],"texture,":[128],"further":[130],"measure":[131],"patch":[137,159],"by":[138,169,204],"extracting":[139],"matching":[141],"structure":[144],"(using":[145,154],"binary":[146],"Gabor":[147],"pattern":[148],"(BGP))":[149],"color":[152,155],"features":[153],"histograms)":[156],"between":[157],"its":[161,212],"sub-regions.":[162],"Finally,":[163],"obtain":[165],"scoring":[170],"ranking":[172],"extracted":[173],"using":[175],"these":[176],"We":[182],"evaluate":[183],"our":[184],"variety":[188],"different":[192],"kinds":[193],"textures.":[195],"A":[196],"convincing":[197],"visual":[198],"comparison":[199],"textures":[201],"manually":[202],"selected":[203],"artist":[206],"statistical":[209],"study":[210],"demonstrate":[211],"effectiveness.":[213]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}