{"id":"https://openalex.org/W2124090140","doi":"https://doi.org/10.1109/etfa.2008.4638397","title":"Application-based approach for automatic texture defect recognition on synthetic surfaces","display_name":"Application-based approach for automatic texture defect recognition on synthetic surfaces","publication_year":2008,"publication_date":"2008-09-01","ids":{"openalex":"https://openalex.org/W2124090140","doi":"https://doi.org/10.1109/etfa.2008.4638397","mag":"2124090140"},"language":"en","primary_location":{"id":"doi:10.1109/etfa.2008.4638397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2008.4638397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Emerging Technologies and Factory Automation","raw_type":"proceedings-article"},"type":"article","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/A5097433248","display_name":"Marcus Niederhofer","orcid":null},"institutions":[{"id":"https://openalex.org/I78801874","display_name":"Phoenix Contact (United States)","ror":"https://ror.org/02av1as94","country_code":"US","type":"company","lineage":["https://openalex.org/I4210155348","https://openalex.org/I78801874"]},{"id":"https://openalex.org/I4210155348","display_name":"Phoenix Contact (Germany)","ror":"https://ror.org/04z7k0065","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210155348"]}],"countries":["DE","US"],"is_corresponding":true,"raw_author_name":"Marcus Niederhofer","raw_affiliation_strings":["Phoenix Contact GmbH and Company KG, Blomberg, Germany","Phoenix Contact GmbH & Co. KG, Blomberg"],"affiliations":[{"raw_affiliation_string":"Phoenix Contact GmbH and Company KG, Blomberg, Germany","institution_ids":["https://openalex.org/I4210155348"]},{"raw_affiliation_string":"Phoenix Contact GmbH & Co. KG, Blomberg","institution_ids":["https://openalex.org/I78801874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003230577","display_name":"Volker Lohweg","orcid":"https://orcid.org/0000-0002-3325-7887"},"institutions":[{"id":"https://openalex.org/I5209920","display_name":"Ostwestfalen-Lippe University of Applied Sciences and Arts","ror":"https://ror.org/04eka8j06","country_code":"DE","type":"education","lineage":["https://openalex.org/I5209920"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Volker Lohweg","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Institute Industrial IT, Ostwestfalen-Lippe University of Applied Sciences, Lemgo, Germany","Ostwestfalen-Lippe, University of Applied Sciences, Department of Electrical Engineering and Computer Science, Institute Industrial IT, Liebigstra\u00dfe 87, 32657 Lemgo, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Institute Industrial IT, Ostwestfalen-Lippe University of Applied Sciences, Lemgo, Germany","institution_ids":["https://openalex.org/I5209920"]},{"raw_affiliation_string":"Ostwestfalen-Lippe, University of Applied Sciences, Department of Electrical Engineering and Computer Science, Institute Industrial IT, Liebigstra\u00dfe 87, 32657 Lemgo, Germany","institution_ids":["https://openalex.org/I5209920"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5097433248"],"corresponding_institution_ids":["https://openalex.org/I4210155348","https://openalex.org/I78801874"],"apc_list":null,"apc_paid":null,"fwci":2.4746,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.89640673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"229","last_page":"232"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9815000295639038,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9735000133514404,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7775357961654663},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.738791286945343},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.7380701303482056},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7048512697219849},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.632799506187439},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.5856307148933411},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5772596001625061},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5685028433799744},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.4530586004257202},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4397377371788025},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.42775875329971313},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39591556787490845},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17971184849739075}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7775357961654663},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.738791286945343},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.7380701303482056},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7048512697219849},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.632799506187439},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.5856307148933411},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5772596001625061},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5685028433799744},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.4530586004257202},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4397377371788025},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42775875329971313},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39591556787490845},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17971184849739075},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/etfa.2008.4638397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa.2008.4638397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Emerging Technologies and Factory Automation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1481408149","https://openalex.org/W1490760466","https://openalex.org/W1587163849","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W1963850344","https://openalex.org/W2033769372","https://openalex.org/W2044465660","https://openalex.org/W2072930813","https://openalex.org/W2132864254","https://openalex.org/W4239875977"],"related_works":["https://openalex.org/W4360784979","https://openalex.org/W2204605857","https://openalex.org/W2044270176","https://openalex.org/W1996489018","https://openalex.org/W2120981610","https://openalex.org/W2007664797","https://openalex.org/W3129669851","https://openalex.org/W2374828682","https://openalex.org/W2360759360","https://openalex.org/W2065064759"],"abstract_inverted_index":{"Synthetic":[0],"surfaces,":[1],"in":[2,16],"particular":[3],"polymer":[4],"structures,":[5],"which":[6],"are":[7],"used":[8],"for":[9,30],"electronic":[10],"components,":[11],"have":[12],"to":[13,112],"be":[14,71,123],"inspected":[15,114],"industrial":[17],"processes.":[18],"Polymers":[19],"show":[20],"some":[21],"specific":[22],"surface":[23,36],"characteristics.":[24],"This":[25],"a-priori":[26],"knowledge":[27],"is":[28,45,60,97],"useable":[29],"the":[31,58,75,78,83,101,104,113],"feature":[32,43,106],"extraction":[33,44],"of":[34,77,85,93,103],"a":[35,39,63,94],"texture":[37,121],"and":[38,54,81],"following":[40],"classification.":[41],"The":[42,91],"performed":[46],"by":[47,62,99],"using":[48],"statistical":[49],"information,":[50],"calculated":[51],"from":[52,108],"sum":[53],"difference":[55],"histograms,":[56],"while":[57],"classification":[59,92],"executed":[61],"fuzzy":[64],"pattern":[65],"classifier.":[66],"A":[67],"defect":[68,95],"area":[69],"can":[70],"recognized":[72],"just":[73],"on":[74],"basis":[76],"tested":[79],"image":[80],"without":[82],"need":[84],"any":[86],"further":[87],"reference":[88],"learning":[89],"data.":[90],"part":[96],"achieved":[98],"analyzing":[100],"divergence":[102],"extracted":[105],"values":[107],"their":[109],"median":[110],"related":[111],"area.":[115],"Surfaces":[116],"that":[117],"contain":[118],"an":[119],"inconsistent":[120],"will":[122],"rejected.":[124]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
