{"id":"https://openalex.org/W2902287439","doi":"https://doi.org/10.1109/icpr.2018.8545719","title":"Multi-Scale Cross-Band Encoding of Sectored Local Binary Pattern for Robust Texture Classification","display_name":"Multi-Scale Cross-Band Encoding of Sectored Local Binary Pattern for Robust Texture Classification","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902287439","doi":"https://doi.org/10.1109/icpr.2018.8545719","mag":"2902287439"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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/A5010200502","display_name":"Tiecheng Song","orcid":"https://orcid.org/0000-0003-1264-2812"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiecheng Song","raw_affiliation_strings":["School of Communication and information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communication and information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701650","display_name":"Lin Luo","orcid":"https://orcid.org/0000-0002-4349-4595"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Luo","raw_affiliation_strings":["School of Communication and information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communication and information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035555813","display_name":"Liangliang Xin","orcid":"https://orcid.org/0009-0009-1239-2586"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangliang Xin","raw_affiliation_strings":["School of Communication and information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communication and information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021881939","display_name":"Chenqiang Gao","orcid":"https://orcid.org/0000-0003-4174-4148"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenqiang Gao","raw_affiliation_strings":["School of Communication and information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communication and information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":null,"first_page":"1163","last_page":"1168"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9991999864578247,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9991999864578247,"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":0.996399998664856,"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/T10057","display_name":"Face and Expression Recognition","score":0.9854999780654907,"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/local-binary-patterns","display_name":"Local binary patterns","score":0.9167158603668213},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.8037459254264832},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7868791818618774},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7565377950668335},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6740686893463135},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5179792642593384},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5114792585372925},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5039491057395935},{"id":"https://openalex.org/keywords/binary-code","display_name":"Binary code","score":0.48372629284858704},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.4365423023700714},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43223845958709717},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41637712717056274},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3825094699859619},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37067800760269165},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21377938985824585}],"concepts":[{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.9167158603668213},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.8037459254264832},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7868791818618774},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7565377950668335},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6740686893463135},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5179792642593384},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5114792585372925},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5039491057395935},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.48372629284858704},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.4365423023700714},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43223845958709717},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41637712717056274},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3825094699859619},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37067800760269165},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21377938985824585},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8545719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1901075642","https://openalex.org/W2000123870","https://openalex.org/W2023827188","https://openalex.org/W2028735463","https://openalex.org/W2030576021","https://openalex.org/W2034017214","https://openalex.org/W2034568153","https://openalex.org/W2036074118","https://openalex.org/W2046720219","https://openalex.org/W2052446636","https://openalex.org/W2058021621","https://openalex.org/W2058160332","https://openalex.org/W2086005648","https://openalex.org/W2098347925","https://openalex.org/W2117251230","https://openalex.org/W2118213141","https://openalex.org/W2131081720","https://openalex.org/W2147141800","https://openalex.org/W2152548630","https://openalex.org/W2159988601","https://openalex.org/W2163352848","https://openalex.org/W2171134985","https://openalex.org/W2309104975","https://openalex.org/W2409822643","https://openalex.org/W2411338455","https://openalex.org/W2580081062","https://openalex.org/W2590762055","https://openalex.org/W6659718465"],"related_works":["https://openalex.org/W2104492225","https://openalex.org/W1990254706","https://openalex.org/W2404514746","https://openalex.org/W1843372508","https://openalex.org/W2581696209","https://openalex.org/W2020430625","https://openalex.org/W2044065526","https://openalex.org/W2058306460","https://openalex.org/W2955952267","https://openalex.org/W2083564146"],"abstract_inverted_index":{"The":[0],"original":[1],"Local":[2,32,79],"Binary":[3,33,80],"Pattern":[4,34,81],"(LBP)":[5],"has":[6],"limited":[7],"discriminative":[8,57],"power":[9],"and":[10,50,67,125,141],"is":[11,44,83,103],"sensitive":[12],"to":[13,46,85],"noise.":[14,150],"In":[15],"view":[16],"of":[17,30,108,145,148],"this.,":[18],"this":[19],"paper":[20],"proposes":[21],"a":[22,76,99],"novel":[23],"image":[24],"descriptor":[25],"called":[26],"Multi-Scale":[27],"Cross-Band":[28],"Encoding":[29],"Sectored":[31,78],"(MCE-SLBP)":[35],"for":[36],"robust":[37,77],"texture":[38,87,109,120],"classification.":[39],"First.,":[40],"the":[41,72,91,129,133,143],"pyramid":[42],"decomposition":[43,114],"explored":[45],"obtain":[47],"multi-scale":[48,100],"low-frequency":[49],"high-frequency":[51,60,69],"(difference)":[52],"images.":[53],"To":[54],"encode":[55],"more":[56],"features.,":[58],"these":[59],"images":[61,70,93],"are":[62],"further":[63],"decomposed":[64,92],"into":[65],"positive":[66],"negative":[68],"via":[71,94],"polarity":[73],"splitting.":[74],"Then.,":[75],"(SLBP)":[82],"proposed":[84,130],"compute":[86],"feature":[88],"codes":[89,110],"on":[90,117],"cross-band":[95],"joint":[96],"coding.":[97],"Finally.,":[98],"histogram":[101],"representation":[102],"obtained":[104],"by":[105],"concatenating":[106],"histograms":[107],"computed":[111],"at":[112],"all":[113],"levels.":[115],"Experiments":[116],"three":[118],"benchmark":[119],"databases":[121],"(i.e..,":[122],"Outex.,":[123],"Brodatz":[124],"CUReT)":[126],"demonstrate":[127],"that":[128],"method":[131],"achieves":[132],"state-of-the-art":[134],"classification":[135],"accuracies":[136],"both":[137],"under":[138],"noise-free":[139],"conditions":[140],"in":[142],"presence":[144],"different":[146],"levels":[147],"Gaussian":[149]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
