{"id":"https://openalex.org/W2009742404","doi":"https://doi.org/10.1109/fcv.2013.6485491","title":"Urban road extraction based on hough transform and region growing","display_name":"Urban road extraction based on hough transform and region growing","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W2009742404","doi":"https://doi.org/10.1109/fcv.2013.6485491","mag":"2009742404"},"language":"en","primary_location":{"id":"doi:10.1109/fcv.2013.6485491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fcv.2013.6485491","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision","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/A5030558643","display_name":"Darlis Herumurti","orcid":"https://orcid.org/0000-0001-5865-796X"},"institutions":[{"id":"https://openalex.org/I96036126","display_name":"Kumamoto University","ror":"https://ror.org/02cgss904","country_code":"JP","type":"education","lineage":["https://openalex.org/I96036126"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Darlis Herumurti","raw_affiliation_strings":["Graduate School of Science and Technology, Kumamoto University, Kumamoto, Japan","Grad. Sch. of Sci. & Technol., Kumamoto Univ., Kumamoto, Japan#TAB#"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Kumamoto University, Kumamoto, Japan","institution_ids":["https://openalex.org/I96036126"]},{"raw_affiliation_string":"Grad. Sch. of Sci. & Technol., Kumamoto Univ., Kumamoto, Japan#TAB#","institution_ids":["https://openalex.org/I96036126"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113818116","display_name":"Keiichi Uchimura","orcid":null},"institutions":[{"id":"https://openalex.org/I96036126","display_name":"Kumamoto University","ror":"https://ror.org/02cgss904","country_code":"JP","type":"education","lineage":["https://openalex.org/I96036126"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keiichi Uchimura","raw_affiliation_strings":["Graduate School of Science and Technology, Kumamoto University, Kumamoto, Japan","Grad. Sch. of Sci. & Technol., Kumamoto Univ., Kumamoto, Japan#TAB#"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Kumamoto University, Kumamoto, Japan","institution_ids":["https://openalex.org/I96036126"]},{"raw_affiliation_string":"Grad. Sch. of Sci. & Technol., Kumamoto Univ., Kumamoto, Japan#TAB#","institution_ids":["https://openalex.org/I96036126"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016988662","display_name":"Gou Koutaki","orcid":"https://orcid.org/0000-0002-3414-1085"},"institutions":[{"id":"https://openalex.org/I96036126","display_name":"Kumamoto University","ror":"https://ror.org/02cgss904","country_code":"JP","type":"education","lineage":["https://openalex.org/I96036126"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Gou Koutaki","raw_affiliation_strings":["Graduate School of Science and Technology, Kumamoto University, Kumamoto, Japan","Grad. Sch. of Sci. & Technol., Kumamoto Univ., Kumamoto, Japan#TAB#"],"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Kumamoto University, Kumamoto, Japan","institution_ids":["https://openalex.org/I96036126"]},{"raw_affiliation_string":"Grad. Sch. of Sci. & Technol., Kumamoto Univ., Kumamoto, Japan#TAB#","institution_ids":["https://openalex.org/I96036126"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102101734","display_name":"Takumi Uemura","orcid":null},"institutions":[{"id":"https://openalex.org/I181097317","display_name":"Sojo University","ror":"https://ror.org/014fz7968","country_code":"JP","type":"education","lineage":["https://openalex.org/I181097317"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takumi Uemura","raw_affiliation_strings":["Faculty of Computer and Information Science, Sojo University, Kumamoto, Japan","Fac. of Comput. & Inf. Sci., Sojo Univ., Kumamoto, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer and Information Science, Sojo University, Kumamoto, Japan","institution_ids":["https://openalex.org/I181097317"]},{"raw_affiliation_string":"Fac. of Comput. & Inf. Sci., Sojo Univ., Kumamoto, Japan","institution_ids":["https://openalex.org/I181097317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5030558643"],"corresponding_institution_ids":["https://openalex.org/I96036126"],"apc_list":null,"apc_paid":null,"fwci":4.1308,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.92750547,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"220","last_page":"224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T13282","display_name":"Automated Road and Building Extraction","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.9804999828338623,"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/hough-transform","display_name":"Hough transform","score":0.8613408207893372},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.7383543252944946},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.625426709651947},{"id":"https://openalex.org/keywords/elevation","display_name":"Elevation (ballistics)","score":0.6214296221733093},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6161225438117981},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6142981648445129},{"id":"https://openalex.org/keywords/shadow","display_name":"Shadow (psychology)","score":0.608558177947998},{"id":"https://openalex.org/keywords/road-surface","display_name":"Road surface","score":0.5932183265686035},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.5567799210548401},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5248392224311829},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5182895064353943},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.4425755739212036},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3237859010696411},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.25930657982826233},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15599927306175232},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14541399478912354}],"concepts":[{"id":"https://openalex.org/C200518788","wikidata":"https://www.wikidata.org/wiki/Q195076","display_name":"Hough transform","level":3,"score":0.8613408207893372},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7383543252944946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.625426709651947},{"id":"https://openalex.org/C37054046","wikidata":"https://www.wikidata.org/wiki/Q641888","display_name":"Elevation (ballistics)","level":2,"score":0.6214296221733093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6161225438117981},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6142981648445129},{"id":"https://openalex.org/C117797892","wikidata":"https://www.wikidata.org/wiki/Q286363","display_name":"Shadow (psychology)","level":2,"score":0.608558177947998},{"id":"https://openalex.org/C2780042925","wikidata":"https://www.wikidata.org/wiki/Q1049667","display_name":"Road surface","level":2,"score":0.5932183265686035},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.5567799210548401},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5248392224311829},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5182895064353943},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.4425755739212036},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3237859010696411},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25930657982826233},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15599927306175232},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14541399478912354},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fcv.2013.6485491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fcv.2013.6485491","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W203741292","https://openalex.org/W1951121370","https://openalex.org/W2021566651","https://openalex.org/W2095905764","https://openalex.org/W2098180043","https://openalex.org/W4285719527","https://openalex.org/W6608365309","https://openalex.org/W6641027433"],"related_works":["https://openalex.org/W2030098947","https://openalex.org/W1974777989","https://openalex.org/W2363834444","https://openalex.org/W2003466055","https://openalex.org/W2070077862","https://openalex.org/W2765199790","https://openalex.org/W2164944168","https://openalex.org/W2326760703","https://openalex.org/W262984167","https://openalex.org/W1575739303"],"abstract_inverted_index":{"In":[0,21],"the":[1,15,35,46,57,67,71,86,93,97,100,103,116,120,130,147,154,165,168,176,188,197,201],"paper,":[2],"we":[3,24,122,145],"present":[4],"an":[5,63,78],"approach":[6],"of":[7,37,48,84,96,109,115,167],"road":[8,58,80,101,131,155,185],"extraction":[9],"in":[10,55,59,89],"urban":[11,60,90],"area":[12,61,91],"by":[13,70,172,186],"combining":[14],"Hough":[16,124],"transform":[17,125],"and":[18,41,102,128,135],"region":[19,149,160],"growing.":[20],"this":[22,110,137],"case,":[23],"use":[25,123,136,146],"Digital":[26],"Surface":[27],"Mode":[28],"(DSM)":[29],"data,":[30],"which":[31],"is":[32,66,92,179],"based":[33],"on":[34,43],"elevation":[36,98],"land":[38],"surface,":[39],"building,":[40],"so":[42],"to":[44,77,126,139,152,181],"overcome":[45],"disadvantage":[47],"aerial":[49,64],"photo":[50,65],"image.":[51],"The":[52,73,157,192],"main":[53],"problem":[54],"extracting":[56],"from":[62,164],"shadow":[68,74],"cast":[69],"buildings.":[72],"will":[75],"lead":[76],"inappropriate":[79],"segment.":[81],"Another":[82],"benefit":[83],"using":[85],"DSM":[87],"data":[88,111],"significant":[94],"different":[95],"between":[99],"building":[104],"elevation.":[105],"A":[106],"simple":[107],"thresholding":[108],"could":[112],"extract":[113],"some":[114],"road.":[117],"To":[118],"improve":[119],"result,":[121],"detect":[127],"recognize":[129],"as":[132],"a":[133,141,183,205],"line":[134],"information":[138],"make":[140],"better":[142],"threshold.":[143],"Furthermore,":[144],"seeding":[148],"growing":[150,161],"method":[151,199],"expand":[153],"network.":[156],"seeds":[158],"for":[159],"are":[162],"obtained":[163],"perimeter":[166],"threshold":[169],"segmentation":[170],"resulted":[171],"hough":[173],"lines.":[174],"Finally,":[175],"post":[177],"processing":[178],"required":[180],"remove":[182],"false":[184],"employing":[187],"morphology":[189],"image":[190],"operator.":[191],"experiment":[193],"result":[194,203],"shows":[195],"that":[196],"proposed":[198],"improves":[200],"quality":[202],"with":[204],"very":[206],"good":[207],"performance.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
