{"id":"https://openalex.org/W2111205070","doi":"https://doi.org/10.1109/robot.2008.4543816","title":"Automated data processing for a rapid 3D surface inspection system","display_name":"Automated data processing for a rapid 3D surface inspection system","publication_year":2008,"publication_date":"2008-05-01","ids":{"openalex":"https://openalex.org/W2111205070","doi":"https://doi.org/10.1109/robot.2008.4543816","mag":"2111205070"},"language":"en","primary_location":{"id":"doi:10.1109/robot.2008.4543816","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robot.2008.4543816","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 Robotics and Automation","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/A5101673535","display_name":"Quan Shi","orcid":"https://orcid.org/0000-0001-5024-9128"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Quan Shi","raw_affiliation_strings":["Electrical and Computer Engineering, Michigan State University, East Lansing, MI, USA","Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023212284","display_name":"Ning Xi","orcid":"https://orcid.org/0000-0001-8276-5696"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ning Xi","raw_affiliation_strings":["Electrical and Computer Engineering, Michigan State University, East Lansing, MI, USA","Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87216513"],"apc_list":null,"apc_paid":null,"fwci":2.346,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.9043952,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3939","last_page":"3944"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9998000264167786,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9998000264167786,"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/T11583","display_name":"Advanced Measurement and Metrology Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8946022391319275},{"id":"https://openalex.org/keywords/iterative-closest-point","display_name":"Iterative closest point","score":0.8103249073028564},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7224763631820679},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6793577671051025},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6594109535217285},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6258852481842041},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.534318745136261},{"id":"https://openalex.org/keywords/ransac","display_name":"RANSAC","score":0.49099138379096985},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4906729459762573},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.4453733563423157},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4368188679218292},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4271218180656433},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16098052263259888},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14333271980285645}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8946022391319275},{"id":"https://openalex.org/C195958017","wikidata":"https://www.wikidata.org/wiki/Q1675268","display_name":"Iterative closest point","level":3,"score":0.8103249073028564},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7224763631820679},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6793577671051025},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6594109535217285},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6258852481842041},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.534318745136261},{"id":"https://openalex.org/C114744707","wikidata":"https://www.wikidata.org/wiki/Q218533","display_name":"RANSAC","level":3,"score":0.49099138379096985},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4906729459762573},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.4453733563423157},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4368188679218292},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4271218180656433},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16098052263259888},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14333271980285645},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/robot.2008.4543816","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robot.2008.4543816","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 Robotics and Automation","raw_type":"proceedings-article"},{"id":"pmh:oai:hub.hku.hk:10722/213004","is_oa":false,"landing_page_url":"http://hdl.handle.net/10722/213004","pdf_url":null,"source":{"id":"https://openalex.org/S4377196271","display_name":"The HKU Scholars Hub (University of Hong Kong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I889458895","host_organization_name":"University of Hong Kong","host_organization_lineage":["https://openalex.org/I889458895"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference_Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320307103","display_name":"Ford Motor Company","ror":"https://ror.org/00g2tkw06"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1563672609","https://openalex.org/W1971363475","https://openalex.org/W2027169910","https://openalex.org/W2037127694","https://openalex.org/W2048876827","https://openalex.org/W2049981393","https://openalex.org/W2152791871","https://openalex.org/W2157769990","https://openalex.org/W2611684114","https://openalex.org/W6643033991","https://openalex.org/W6682347070"],"related_works":["https://openalex.org/W2769402452","https://openalex.org/W2091258128","https://openalex.org/W4385261474","https://openalex.org/W3171899115","https://openalex.org/W1983540692","https://openalex.org/W3126266918","https://openalex.org/W2813834476","https://openalex.org/W4239102697","https://openalex.org/W4391129294","https://openalex.org/W3016861202"],"abstract_inverted_index":{"For":[0,32,194],"3D":[1],"dimensional":[2],"inspection":[3,178,220],"systems,":[4],"point":[5,47,67,76,103,129,152,188,212],"clouds":[6,153,189],"measured":[7,75],"on":[8,225],"each":[9],"viewpoint":[10],"need":[11],"to":[12,42,55,80,114,158,171,213],"be":[13,43,155,181],"processed":[14],"for":[15,69,162],"quality":[16,33],"evaluation.":[17],"Three":[18],"steps":[19],"are":[20,232],"usually":[21],"included":[22],"in":[23,45,125,187,203,234],"this":[24,148,204,235],"process:":[25],"filtering,":[26],"registration,":[27],"and":[28,39,59,116],"error":[29,100,195],"map":[30,196],"generation.":[31],"control,":[34],"small":[35],"defects":[36],"like":[37],"dints":[38],"dents":[40],"have":[41],"kept":[44],"the":[46,66,74,82,85,99,143,150,176,208],"cloud.":[48],"Therefore,":[49],"a":[50,110,159,198,211,226],"filtering":[51,63,105,121],"algorithm":[52,64,106,113],"is":[53,78,92,107,122,201],"required":[54],"automatically":[56,182],"remove":[57,117],"outliers":[58,137],"keep":[60],"dints/dents.":[61],"Many":[62],"smooth":[65],"cloud":[68,77,104,120],"better":[70],"display,":[71],"however,":[72],"since":[73],"used":[79,202],"represent":[81],"shape":[83],"of":[84,88,210],"part,":[86],"modification":[87],"any":[89],"point's":[90],"coordinates":[91],"not":[93],"allowed":[94],"because":[95,136],"that":[96],"will":[97,138],"modify":[98],"map.":[101],"A":[102],"developed":[108],"using":[109],"link":[111],"clustering":[112],"identify":[115],"outliers.":[118],"Point":[119],"especially":[123],"important":[124],"an":[126],"iterative":[127],"closest":[128,215],"(ICP)-based":[130],"robot":[131,228],"hand-":[132],"eye":[133],"calibration":[134,140],"method":[135,166],"bring":[139],"errors":[141],"into":[142],"calculated":[144],"transformation":[145],"matrix.":[146],"With":[147],"technique,":[149],"cleaned":[151],"can":[154,180],"directly":[156],"transformed":[157],"world":[160],"frame":[161],"registration.":[163],"This":[164],"registration":[165,173],"has":[167],"two":[168],"advantages":[169],"compared":[170],"feature-based":[172],"methods:":[174],"1)":[175],"entire":[177],"process":[179],"executed,":[183],"2)":[184],"avoid":[185],"holes":[186],"caused":[190],"by":[191],"artificial":[192],"markers.":[193],"generation,":[197],"point-to-plane":[199],"distance":[200,209],"paper":[205],"which":[206],"calculates":[207],"its":[214],"triangle.":[216],"The":[217],"introduced":[218],"automated":[219],"system":[221],"had":[222],"been":[223],"implemented":[224],"PUMA":[227],"system.":[229],"Experimental":[230],"results":[231],"described":[233],"paper.":[236]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}