{"id":"https://openalex.org/W1627073440","doi":"https://doi.org/10.1109/icinfa.2015.7279369","title":"Pavement detection in YCbCr color space and its application","display_name":"Pavement detection in YCbCr color space and its application","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W1627073440","doi":"https://doi.org/10.1109/icinfa.2015.7279369","mag":"1627073440"},"language":"en","primary_location":{"id":"doi:10.1109/icinfa.2015.7279369","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icinfa.2015.7279369","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Information and 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/A5088641929","display_name":"Yu-Kumg Chen","orcid":"https://orcid.org/0009-0004-6313-9197"},"institutions":[{"id":"https://openalex.org/I202968851","display_name":"Huafan University","ror":"https://ror.org/02x5hb316","country_code":"TW","type":"education","lineage":["https://openalex.org/I202968851"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Yu-Kumg Chen","raw_affiliation_strings":["Department of Electronic Engineering, Huafan University, New Taipei City, Taiwan","Department of Electronic Engineering, Huafan University, New Taipei City 223, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Huafan University, New Taipei City, Taiwan","institution_ids":["https://openalex.org/I202968851"]},{"raw_affiliation_string":"Department of Electronic Engineering, Huafan University, New Taipei City 223, Taiwan","institution_ids":["https://openalex.org/I202968851"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071671494","display_name":"Kuan\u2010Jung Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I202968851","display_name":"Huafan University","ror":"https://ror.org/02x5hb316","country_code":"TW","type":"education","lineage":["https://openalex.org/I202968851"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Kuan-Jung Chen","raw_affiliation_strings":["Department of Electronic Engineering, Huafan University, New Taipei City, Taiwan","Department of Electronic Engineering, Huafan University, New Taipei City 223, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Huafan University, New Taipei City, Taiwan","institution_ids":["https://openalex.org/I202968851"]},{"raw_affiliation_string":"Department of Electronic Engineering, Huafan University, New Taipei City 223, Taiwan","institution_ids":["https://openalex.org/I202968851"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088641929"],"corresponding_institution_ids":["https://openalex.org/I202968851"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.03649673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"663","last_page":"667"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11019","display_name":"Image Enhancement Techniques","score":0.9937000274658203,"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/T11666","display_name":"Color Science and Applications","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.7501747608184814},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7475622892379761},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.741752564907074},{"id":"https://openalex.org/keywords/ycbcr","display_name":"YCbCr","score":0.6856290698051453},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6725764274597168},{"id":"https://openalex.org/keywords/color-space","display_name":"Color space","score":0.5783646702766418},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4188598692417145},{"id":"https://openalex.org/keywords/color-image","display_name":"Color image","score":0.348926305770874},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3196052312850952},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1522795557975769},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.10063457489013672}],"concepts":[{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.7501747608184814},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7475622892379761},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.741752564907074},{"id":"https://openalex.org/C2779407163","wikidata":"https://www.wikidata.org/wiki/Q1189998","display_name":"YCbCr","level":5,"score":0.6856290698051453},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6725764274597168},{"id":"https://openalex.org/C2961294","wikidata":"https://www.wikidata.org/wiki/Q166863","display_name":"Color space","level":3,"score":0.5783646702766418},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4188598692417145},{"id":"https://openalex.org/C142616399","wikidata":"https://www.wikidata.org/wiki/Q5148604","display_name":"Color image","level":4,"score":0.348926305770874},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3196052312850952},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1522795557975769},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.10063457489013672}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icinfa.2015.7279369","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icinfa.2015.7279369","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Information and Automation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7900000214576721,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1486754293","https://openalex.org/W1496431500","https://openalex.org/W1555540232","https://openalex.org/W1965887009","https://openalex.org/W1973228964","https://openalex.org/W2019309423","https://openalex.org/W2021564380","https://openalex.org/W2065463049","https://openalex.org/W2980909807","https://openalex.org/W2982554162","https://openalex.org/W3162111397"],"related_works":["https://openalex.org/W1966264553","https://openalex.org/W3107671540","https://openalex.org/W2939643258","https://openalex.org/W2382798019","https://openalex.org/W4387912986","https://openalex.org/W2124642465","https://openalex.org/W2888369944","https://openalex.org/W2086128134","https://openalex.org/W3032257599","https://openalex.org/W2382121072"],"abstract_inverted_index":{"Recognition":[0],"of":[1,20,63,94,106,122],"driving-view":[2,25,107],"image":[3,26],"is":[4,18,70],"the":[5,21,33,39,48,60,66,80,92,119,123],"most":[6],"important":[7,22],"future":[8],"issue":[9],"in":[10,24,32,38,53,65,72],"a":[11],"smart":[12],"tachograph.":[13],"The":[14],"intersection":[15,103],"imaging":[16,51,104],"recognition":[17,52,105],"one":[19],"issues":[23],"recognition.":[27],"In":[28],"addition":[29],"to":[30,47,102,117],"using":[31,86],"GPS":[34],"satellite":[35],"positioning":[36],"correction":[37],"metropolitan":[40],"area,":[41],"it":[42,98],"can":[43,82,99],"also":[44],"be":[45,83,100],"applied":[46,101],"traffic":[49],"lights":[50],"an":[54],"intersection.":[55],"With":[56],"some":[57,114],"samples":[58],"analyzing,":[59],"color":[61,68,88],"ranges":[62],"pavement":[64,76],"YCbCr":[67],"space":[69],"developed":[71],"this":[73,87],"paper.":[74],"Therefore,":[75],"and":[77,90,96],"markings":[78,95],"on":[79],"road":[81],"separated.":[84],"By":[85],"separation":[89],"calculating":[91],"ratio":[93],"pavement,":[97],"image.":[108],"Experiments":[109],"are":[110],"carried":[111],"out":[112],"for":[113],"VEDR's":[115],"videos":[116],"demonstration":[118],"computational":[120],"advantage":[121],"proposed":[124],"method.":[125]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
