{"id":"https://openalex.org/W1991183060","doi":"https://doi.org/10.1186/1687-5281-2013-17","title":"Evaluation of noise robustness for local binary pattern descriptors in texture classification","display_name":"Evaluation of noise robustness for local binary pattern descriptors in texture classification","publication_year":2013,"publication_date":"2013-04-15","ids":{"openalex":"https://openalex.org/W1991183060","doi":"https://doi.org/10.1186/1687-5281-2013-17","mag":"1991183060"},"language":"en","primary_location":{"id":"doi:10.1186/1687-5281-2013-17","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-5281-2013-17","pdf_url":"https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-5281-2013-17","source":{"id":"https://openalex.org/S153767265","display_name":"EURASIP Journal on Image and Video Processing","issn_l":"1687-5176","issn":["1687-5176","1687-5281"],"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":"EURASIP Journal on Image and Video Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-5281-2013-17","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004591767","display_name":"Gustaf Kylberg","orcid":null},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Gustaf Kylberg","raw_affiliation_strings":["Centre for Image Analysis, Uppsala University, Uppsala, Sweden","Centre for Image Analysis, Uppsala University, Uppsala, Sweden,"],"affiliations":[{"raw_affiliation_string":"Centre for Image Analysis, Uppsala University, Uppsala, Sweden","institution_ids":["https://openalex.org/I123387679"]},{"raw_affiliation_string":"Centre for Image Analysis, Uppsala University, Uppsala, Sweden,","institution_ids":["https://openalex.org/I123387679"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075025484","display_name":"Ida\u2010Maria Sintorn","orcid":"https://orcid.org/0000-0002-8307-7411"},"institutions":[{"id":"https://openalex.org/I298625061","display_name":"Swedish University of Agricultural Sciences","ror":"https://ror.org/02yy8x990","country_code":"SE","type":"education","lineage":["https://openalex.org/I298625061"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Ida-Maria Sintorn","raw_affiliation_strings":["Centre for Image Analysis, Swedish University of Agricultural Sciences, Uppsala, Sweden","Centre for Image Analysis, Swedish University of Agricultural Sciences, Uppsala, Sweden#TAB#"],"affiliations":[{"raw_affiliation_string":"Centre for Image Analysis, Swedish University of Agricultural Sciences, Uppsala, Sweden","institution_ids":["https://openalex.org/I298625061"]},{"raw_affiliation_string":"Centre for Image Analysis, Swedish University of Agricultural Sciences, Uppsala, Sweden#TAB#","institution_ids":["https://openalex.org/I298625061"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5004591767"],"corresponding_institution_ids":["https://openalex.org/I123387679"],"apc_list":{"value":1140,"currency":"GBP","value_usd":1398},"apc_paid":{"value":1140,"currency":"GBP","value_usd":1398},"fwci":8.5543,"has_fulltext":true,"cited_by_count":90,"citation_normalized_percentile":{"value":0.98009968,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"2013","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991000294685364,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991000294685364,"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":0.9986000061035156,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.9167934656143188},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7960507273674011},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7083709836006165},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5582305788993835},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.4874260723590851},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.4737582802772522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47065702080726624},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4334101974964142},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4326291084289551},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4110339879989624},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.1393134593963623}],"concepts":[{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.9167934656143188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7960507273674011},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7083709836006165},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5582305788993835},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.4874260723590851},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.4737582802772522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47065702080726624},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4334101974964142},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4326291084289551},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4110339879989624},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.1393134593963623},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/1687-5281-2013-17","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-5281-2013-17","pdf_url":"https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-5281-2013-17","source":{"id":"https://openalex.org/S153767265","display_name":"EURASIP Journal on Image and Video Processing","issn_l":"1687-5176","issn":["1687-5176","1687-5281"],"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":"EURASIP Journal on Image and Video Processing","raw_type":"journal-article"},{"id":"pmh:oai:DiVA.org:uu-203664","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-203664","pdf_url":null,"source":{"id":"https://openalex.org/S4306401559","display_name":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1186/1687-5281-2013-17","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1687-5281-2013-17","pdf_url":"https://jivp-eurasipjournals.springeropen.com/counter/pdf/10.1186/1687-5281-2013-17","source":{"id":"https://openalex.org/S153767265","display_name":"EURASIP Journal on Image and Video Processing","issn_l":"1687-5176","issn":["1687-5176","1687-5281"],"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":"EURASIP Journal on Image and Video Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6200000047683716,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320336376","display_name":"Uppsala Multidisciplinary Center for Advanced Computational Science","ror":null},{"id":"https://openalex.org/F4320338388","display_name":"Eurostars","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1991183060.pdf","grobid_xml":"https://content.openalex.org/works/W1991183060.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W12728872","https://openalex.org/W96182012","https://openalex.org/W150914396","https://openalex.org/W1516748092","https://openalex.org/W1621991092","https://openalex.org/W1972963882","https://openalex.org/W1978011637","https://openalex.org/W2017401249","https://openalex.org/W2023812235","https://openalex.org/W2029927832","https://openalex.org/W2031586513","https://openalex.org/W2039051707","https://openalex.org/W2044465660","https://openalex.org/W2069481589","https://openalex.org/W2072144767","https://openalex.org/W2081362370","https://openalex.org/W2089575713","https://openalex.org/W2094056275","https://openalex.org/W2098305432","https://openalex.org/W2126833203","https://openalex.org/W2130844249","https://openalex.org/W2131081720","https://openalex.org/W2133327040","https://openalex.org/W2138299457","https://openalex.org/W2153786187","https://openalex.org/W2163352848","https://openalex.org/W2164878725","https://openalex.org/W2166690653","https://openalex.org/W2169856283","https://openalex.org/W3016960874","https://openalex.org/W4293768955","https://openalex.org/W4302408070"],"related_works":["https://openalex.org/W2055219403","https://openalex.org/W2791313072","https://openalex.org/W3166997759","https://openalex.org/W2953058328","https://openalex.org/W2794489335","https://openalex.org/W1542224353","https://openalex.org/W2080437822","https://openalex.org/W1661087619","https://openalex.org/W2153027217","https://openalex.org/W2855870609"],"abstract_inverted_index":{"Local":[0],"binary":[1,62],"pattern":[2],"(LBP)":[3],"operators":[4],"have":[5,18],"become":[6],"commonly":[7],"used":[8,38],"texture":[9,144,152,163,189,281],"descriptors":[10,17,41,56,104,145,173,190,208],"in":[11,39],"recent":[12],"years.":[13],"Several":[14],"new":[15,126],"LBP-based":[16,55],"been":[19],"proposed,":[20],"of":[21,118,179,187,196,206,214,226,259,270],"which":[22,128],"some":[23],"aim":[24],"at":[25,211],"improving":[26],"robustness":[27,48],"to":[28,49,90,140,220,251,256,285],"noise.":[29,183,228,272,286],"To":[30,81],"do":[31],"this,":[32],"the":[33,40,47,52,95,119,141,172,188,207,252,264],"thresholding":[34],"and":[35,77,102,124,148,160,233],"encoding":[36],"schemes":[37],"are":[42,57,88,146,174,245],"modified.":[43],"In":[44,110,229,273],"this":[45],"article,":[46],"noise":[50,215,248,260],"for":[51,169],"eight":[53],"following":[54],"evaluated;":[58],"improved":[59,69],"LBP,":[60,76,97],"median":[61],"patterns":[63,67],"(MBP),":[64],"local":[65,72],"ternary":[66],"(LTP),":[68],"LTP":[70],"(ILTP),":[71],"quinary":[73],"patterns,":[74],"robust":[75,249],"fuzzy":[78],"LBP":[79,132],"(FLBP).":[80],"put":[82],"their":[83],"performance":[84,239],"into":[85],"perspective":[86],"they":[87,217],"compared":[89,147,250],"three":[91],"well-known":[92],"reference":[93],"descriptors;":[94],"classic":[96],"Gabor":[98],"filter":[99],"banks":[100],"(GF),":[101],"standard":[103],"derived":[105],"from":[106,223],"gray-level":[107],"co-occurrence":[108],"matrices.":[109],"addition,":[111],"a":[112,125,161,197,279],"roughly":[113],"five":[114],"times":[115],"faster":[116,138],"implementation":[117],"FLBP":[120,234],"descriptor":[121,127,266,282],"is":[122,133,191,277],"presented,":[123],"we":[129],"call":[130],"shift":[131],"introduced":[134,227],"as":[135],"an":[136,236],"even":[137],"approximation":[139],"FLBP.":[142],"The":[143,184,201,243],"evaluated":[149,175],"on":[150,240],"six":[151],"datasets;":[153],"Brodatz,":[154],"KTH-TIPS2b,":[155],"Kylberg,":[156],"Mondial":[157],"Marmi,":[158],"UIUC,":[159],"Virus":[162],"dataset.":[164],"After":[165],"optimizing":[166],"all":[167,218],"parameters":[168],"each":[170],"dataset":[171],"under":[176,254,267],"increasing":[177],"levels":[178,213,225,258,269],"additive":[180],"Gaussian":[181],"white":[182],"discriminating":[185],"power":[186],"assessed":[192],"using":[193],"tenfolded":[194],"cross-validation":[195],"nearest":[198],"neighbor":[199],"classifier.":[200],"results":[202],"show":[203,235],"that":[204],"several":[205,241],"perform":[209],"well":[210],"low":[212,268],"while":[216],"suffer,":[219],"different":[221],"degrees,":[222],"higher":[224],"our":[230,274],"tests,":[231,275],"ILTP":[232],"overall":[237],"good":[238,280],"datasets.":[242],"GF":[244],"often":[246],"very":[247],"LBP-family":[253],"moderate":[255],"high":[257],"but":[261],"not":[262],"necessarily":[263],"best":[265],"added":[271],"MBP":[276],"neither":[278],"nor":[283],"stable":[284]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":15},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":1}],"updated_date":"2026-03-15T09:29:46.208133","created_date":"2025-10-10T00:00:00"}
