{"id":"https://openalex.org/W2963645477","doi":"https://doi.org/10.1109/socpar.2013.7054123","title":"Edge direction matrixes-based local binary patterns descriptor for invariant pattern recognition","display_name":"Edge direction matrixes-based local binary patterns descriptor for invariant pattern recognition","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W2963645477","doi":"https://doi.org/10.1109/socpar.2013.7054123","mag":"2963645477"},"language":"en","primary_location":{"id":"doi:10.1109/socpar.2013.7054123","doi":"https://doi.org/10.1109/socpar.2013.7054123","is_oa":false,"landing_page_url":"https://doi.org/10.1109/socpar.2013.7054123","pdf_url":null,"source":{"id":"https://openalex.org/S7407087228","display_name":"International Conference of Soft Computing and Pattern Recognition (SoCPaR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5033460154","display_name":"Mohammed Ahmed Talab","orcid":"https://orcid.org/0000-0002-7486-1669","observed_orcids":["https://orcid.org/0000-0002-7486-1669"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohammed Ahmed Talab","raw_affiliation_strings":["Faculty of Technology and Information Science, Center for Artificial Intelligence Technology, Bangi, Selangor, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Technology and Information Science, Center for Artificial Intelligence Technology, Bangi, Selangor, Malaysia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051653696","display_name":"Siti Norul Huda Sheikh Abdullah","orcid":"https://orcid.org/0000-0002-2602-7805","observed_orcids":["https://orcid.org/0000-0002-2602-7805"]},"institutions":[{"id":"https://openalex.org/I885383172","display_name":"National University of Malaysia","ror":"https://ror.org/00bw8d226","country_code":"MY","type":"education","lineage":["https://openalex.org/I885383172"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Siti Norul Huda Sheikh Abdullah","raw_affiliation_strings":["Universiti Kebangsaan Malaysia, Bangi, Selangor, MY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universiti Kebangsaan Malaysia, Bangi, Selangor, MY","institution_ids":["https://openalex.org/I885383172"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057304575","display_name":"Mohammad Hakim Assiddiq Razalan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I885383172","display_name":"National University of Malaysia","ror":"https://ror.org/00bw8d226","country_code":"MY","type":"education","lineage":["https://openalex.org/I885383172"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Mohammad Hakim Assiddiq Razalan","raw_affiliation_strings":["Universiti Kebangsaan Malaysia, Bangi, Selangor, MY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universiti Kebangsaan Malaysia, Bangi, Selangor, MY","institution_ids":["https://openalex.org/I885383172"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":1.0,"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":1.0,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.0,"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-pattern","display_name":"local binary pattern","score":0.8299999833106995},{"id":"https://openalex.org/keywords/invariant-descriptors","display_name":"invariant descriptors","score":0.8119999766349792},{"id":"https://openalex.org/keywords/shape-recognition","display_name":"shape recognition","score":0.878000020980835},{"id":"https://openalex.org/keywords/texture-classification","display_name":"texture classification","score":0.9739999771118164},{"id":"https://openalex.org/keywords/arabic-calligraphy","display_name":"Arabic calligraphy","score":0.996999979019165},{"id":"https://openalex.org/keywords/gray-level-co-occurrence-matrix","display_name":"gray level co-occurrence matrix","score":0.8830000162124634},{"id":"https://openalex.org/keywords/sift","display_name":"SIFT","score":0.7260000109672546},{"id":"https://openalex.org/keywords/multilayer-neural-networks","display_name":"multilayer neural networks","score":0.8330000042915344},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.8220000267028809},{"id":"https://openalex.org/keywords/descriptor-fusion","display_name":"descriptor fusion","score":0.49900001287460327}],"concepts":[{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.8441844582557678},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7697319984436035},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7558716535568237},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6201755404472351},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.598421037197113},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5876979231834412},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5141870975494385},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4867367744445801},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.48222434520721436},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3958950638771057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2485692799091339},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1872486174106598},{"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/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/socpar.2013.7054123","doi":"https://doi.org/10.1109/socpar.2013.7054123","is_oa":false,"landing_page_url":"https://doi.org/10.1109/socpar.2013.7054123","pdf_url":null,"source":{"id":"https://openalex.org/S7407087228","display_name":"International Conference of Soft Computing and Pattern Recognition (SoCPaR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W180174940","https://openalex.org/W1487718662","https://openalex.org/W1491922060","https://openalex.org/W1996249507","https://openalex.org/W2032437475","https://openalex.org/W2039051707","https://openalex.org/W2044465660","https://openalex.org/W2049832492","https://openalex.org/W2105026917","https://openalex.org/W2117663372","https://openalex.org/W2119123874","https://openalex.org/W2125614842","https://openalex.org/W2151103935","https://openalex.org/W2303931467","https://openalex.org/W2608800876","https://openalex.org/W2743066794","https://openalex.org/W4206135224","https://openalex.org/W4237313411","https://openalex.org/W4285719527","https://openalex.org/W6737050359"],"related_works":["https://openalex.org/W2027742499","https://openalex.org/W2976207828","https://openalex.org/W1996249507","https://openalex.org/W2899782851","https://openalex.org/W2347942331","https://openalex.org/W2900460335","https://openalex.org/W2743126173","https://openalex.org/W3016573133","https://openalex.org/W2027756614","https://openalex.org/W2947790305"],"abstract_inverted_index":{"Invariant":[0,168],"descriptor":[1,92,195],"for":[2,179,184],"shape":[3,28,180],"and":[4,33,60,63,96,119,132,150,166,181,199],"texture":[5],"image":[6],"recognition":[7,111],"usage":[8],"is":[9,17,80,106],"an":[10,77],"essential":[11],"branch":[12],"of":[13,20,76,103,109,140,192],"pattern":[14],"recognition.":[15],"It":[16,79],"made":[18],"up":[19],"techniques":[21,154],"that":[22],"aim":[23],"at":[24],"extracting":[25],"information":[26,50,62],"from":[27],"images":[29],"via":[30],"human":[31],"knowledge":[32],"works.":[34],"The":[35,100,153,186],"descriptors":[36,125],"need":[37,108],"to":[38,47,71,129,136],"have":[39,188],"strong":[40],"Local":[41,53],"Binary":[42,54],"Pattern":[43,55],"(LBP)":[44,56],"in":[45,156],"order":[46,98],"encode":[48],"the":[49,73,83,107,116,130,134,138,190,193,197,200],"distinguishing":[51],"them.":[52],"ensures":[57],"encoding":[58],"global":[59,90],"local":[61],"scaling":[64],"invariance":[65],"by":[66,115,172],"introducing":[67],"a":[68],"look-up":[69],"table":[70],"reflect":[72],"uniformity":[74],"structure":[75],"object.":[78],"needed":[81],"as":[82],"edge":[84],"direction":[85],"matrices":[86,164],"(EDMS)":[87],"only":[88],"apply":[89],"invariant":[91],"which":[93,113],"employs":[94],"first":[95],"secondary":[97],"relationships.":[99],"main":[101],"objective":[102],"this":[104,157],"paper":[105,158],"improved":[110],"capabilities":[112],"achieved":[114],"combining":[117],"LBP":[118],"EDMS.":[120],"Working":[121],"together,":[122],"these":[123],"two":[124,174],"will":[126],"add":[127],"advantages":[128],"program":[131],"enable":[133],"researcher":[135],"investigate":[137],"weaknesses":[139],"each":[141],"one.":[142],"Two":[143],"classifiers":[144],"are":[145,159],"used:":[146],"multi-layer":[147],"neural":[148],"network":[149],"random":[151],"forest.":[152],"used":[155],"compared":[160],"with":[161],"Gray-Level":[162],"Co-occurrence":[163],"(GLCM-EDMS)":[165],"Scale":[167],"Feature":[169],"Transform":[170],"(SIFT)":[171],"using":[173],"benchmark":[175],"dataset:":[176],"MPEG-7":[177],"CE-Shape-1":[178],"Arabic":[182],"calligraphy":[183],"texture.":[185],"experiments":[187],"shown":[189],"superiority":[191],"introduced":[194],"over":[196],"GLCM-EDMS":[198],"SIFT.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2019-07-30T00:00:00"}