{"id":"https://openalex.org/W2745616385","doi":"https://doi.org/10.1109/icip.2003.1246956","title":"Robust line detection using a weighted MSE estimator","display_name":"Robust line detection using a weighted MSE estimator","publication_year":2004,"publication_date":"2004-06-21","ids":{"openalex":"https://openalex.org/W2745616385","doi":"https://doi.org/10.1109/icip.2003.1246956","mag":"2745616385"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2003.1246956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2003.1246956","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429)","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/A5072131187","display_name":"G.M. Schuster","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127453","display_name":"University of Applied Sciences Rapperswil","ror":"https://ror.org/02g821610","country_code":"CH","type":"education","lineage":["https://openalex.org/I4210127453"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"G.M. Schuster","raw_affiliation_strings":["Abteilung Elektrotechnik, Hochschule Rapperswil, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Abteilung Elektrotechnik, Hochschule Rapperswil, Switzerland","institution_ids":["https://openalex.org/I4210127453"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048650003","display_name":"Aggelos K. Katsaggelos","orcid":"https://orcid.org/0000-0003-4554-0070"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A.K. Katsaggelos","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Northwestern University, Evanston, Illinois, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Northwestern University, Evanston, Illinois, USA","institution_ids":["https://openalex.org/I111979921"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"I","last_page":"293"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection 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/T12549","display_name":"Image and Object Detection 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9919000267982483,"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/robustness","display_name":"Robustness (evolution)","score":0.711003303527832},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6358462572097778},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5973225831985474},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5961245894432068},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.5713653564453125},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.5480102896690369},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5216794013977051},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49609073996543884},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4556454122066498},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.37645813822746277},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3308998942375183},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.33055180311203003},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.28943783044815063},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0699513852596283}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.711003303527832},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6358462572097778},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5973225831985474},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5961245894432068},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.5713653564453125},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.5480102896690369},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5216794013977051},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49609073996543884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4556454122066498},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.37645813822746277},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3308998942375183},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.33055180311203003},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28943783044815063},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0699513852596283},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/icip.2003.1246956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2003.1246956","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429)","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":4,"referenced_works":["https://openalex.org/W1995376165","https://openalex.org/W2104095591","https://openalex.org/W2145023731","https://openalex.org/W2342089072"],"related_works":["https://openalex.org/W4287880334","https://openalex.org/W4366700029","https://openalex.org/W4285230481","https://openalex.org/W4385769873","https://openalex.org/W2015759683","https://openalex.org/W4285411112","https://openalex.org/W3125536267","https://openalex.org/W2274645452","https://openalex.org/W1999706086","https://openalex.org/W2521753262"],"abstract_inverted_index":{"In":[0],"this":[1,79],"paper":[2],"we":[3],"introduce":[4],"a":[5,12,32,65,153,212,219],"novel":[6],"line":[7,34,48,54,66,148,197,221],"detection":[8,49,62,67,72,85],"algorithm":[9,21,124,230],"based":[10],"on":[11,36],"weighted":[13,154,180,209,213],"minimum":[14],"mean":[15],"square":[16],"error":[17],"(MSE)":[18],"formulation.":[19],"This":[20],"has":[22],"been":[23],"developed":[24],"to":[25,30,47,53,89],"enable":[26],"an":[27,60],"autonomous":[28],"robot":[29],"follow":[31],"white":[33],"drawn":[35],"the":[37,70,82,92,99,103,112,119,137,150,164,174,179,188,193,196,203,206,226,229],"floor,":[38],"but":[39],"is":[40,87,149],"general":[41],"in":[42,102,118,130,163,192,205,218,231],"nature":[43],"and":[44,64,105,141,233],"widely":[45],"applicable":[46],"problems.":[50],"Traditional":[51],"approaches":[52],"detections":[55],"consist":[56],"of":[57,136,152,195,228],"two":[58],"stages,":[59],"edge":[61,71,84],"stage":[63,68,86,94,114],"using":[69,133,143],"result.":[73],"There":[74],"are":[75,161],"several":[76],"problems":[77],"with":[78],"approach.":[80],"First,":[81],"initial":[83],"sensitive":[88],"noise.":[90],"Second,":[91],"second":[93,120],"does":[95],"not":[96,142],"use":[97],"all":[98,134],"information":[100],"available":[101],"image":[104,138,207],"there":[106],"fore":[107],"incorrect":[108],"decisions":[109],"made":[110],"by":[111,128],"first":[113],"cannot":[115],"be":[116,171,183,208],"corrected":[117],"stage.":[121],"The":[122,146,157],"proposed":[123],"achieves":[125],"its":[126],"robustness":[127],"operating":[129],"one":[131],"step,":[132],"pixels":[135,204],"(correctly":[139],"weighted)":[140],"any":[144],"thresholds.":[145],"detected":[147],"solution":[151,190,216],"MSE":[155,181,214],"problem.":[156],"following":[158],"three":[159],"questions":[160],"answered":[162],"paper:":[165],"(I)":[166],"what":[167],"mathematical":[168],"model":[169],"should":[170,178,202],"used":[172],"for":[173],"line?":[175],"(II)":[176],"how":[177,201],"problem":[182],"set":[184],"up":[185],"so":[186],"that":[187,211],"optimal":[189,215],"results":[191,217,224],"parameters":[194],"model?":[198],"And":[199],"(III),":[200],"such":[210],"robust":[220],"detection?":[222],"Experimental":[223],"demonstrate":[225],"performance":[227],"noiseless":[232],"noisy":[234],"conditions.":[235]},"counts_by_year":[{"year":2014,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
