{"id":"https://openalex.org/W2983924837","doi":"https://doi.org/10.1109/iisa.2019.8900778","title":"License Plate Extraction for Moving Vehicles","display_name":"License Plate Extraction for Moving Vehicles","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2983924837","doi":"https://doi.org/10.1109/iisa.2019.8900778","mag":"2983924837"},"language":"en","primary_location":{"id":"doi:10.1109/iisa.2019.8900778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iisa.2019.8900778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","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/A5112091880","display_name":"Yongsung Cheon","orcid":null},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Y. Cheon","raw_affiliation_strings":["Yonsei University,Dept. Electrical and Electronic Eng.,Seoul,South Korea","Dept. Electrical and Electronic Eng., Yonsei University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University,Dept. Electrical and Electronic Eng.,Seoul,South Korea","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Dept. Electrical and Electronic Eng., Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109440607","display_name":"C. Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"C. Lee","raw_affiliation_strings":["Yonsei University,Dept. Electrical and Electronic Eng.,Seoul,South Korea","Dept. Electrical and Electronic Eng., Yonsei University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University,Dept. Electrical and Electronic Eng.,Seoul,South Korea","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"Dept. Electrical and Electronic Eng., Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":0.3917,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.54704861,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":1.0,"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"}},{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9966999888420105,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9882000088691711,"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/bhattacharyya-distance","display_name":"Bhattacharyya distance","score":0.7249385118484497},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7068692445755005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6294058561325073},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5831549167633057},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5338066220283508},{"id":"https://openalex.org/keywords/license","display_name":"License","score":0.5288352370262146},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5241872668266296},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.45296457409858704}],"concepts":[{"id":"https://openalex.org/C24145651","wikidata":"https://www.wikidata.org/wiki/Q2901249","display_name":"Bhattacharyya distance","level":2,"score":0.7249385118484497},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7068692445755005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6294058561325073},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5831549167633057},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5338066220283508},{"id":"https://openalex.org/C2780560020","wikidata":"https://www.wikidata.org/wiki/Q79719","display_name":"License","level":2,"score":0.5288352370262146},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5241872668266296},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.45296457409858704},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iisa.2019.8900778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iisa.2019.8900778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1975174385","https://openalex.org/W1975399404","https://openalex.org/W1992732951","https://openalex.org/W2019876754","https://openalex.org/W2040582952","https://openalex.org/W2052735832","https://openalex.org/W2071355008","https://openalex.org/W2111962371","https://openalex.org/W2148528650","https://openalex.org/W2164598857","https://openalex.org/W2165465987","https://openalex.org/W2766910931","https://openalex.org/W4248202654","https://openalex.org/W6655619605","https://openalex.org/W6676359075","https://openalex.org/W6681681983"],"related_works":["https://openalex.org/W3149747767","https://openalex.org/W1536747792","https://openalex.org/W1982681402","https://openalex.org/W2192403599","https://openalex.org/W2366937720","https://openalex.org/W2163087802","https://openalex.org/W2155818328","https://openalex.org/W2121699558","https://openalex.org/W4244450895","https://openalex.org/W2157932304"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,29],"license":[4,50],"plate":[5,51],"extraction":[6],"algorithm":[7],"is":[8],"proposed,":[9],"which":[10],"can":[11],"be":[12],"used":[13,23,33,55,74],"in":[14],"moving":[15],"vehicles.":[16],"First,":[17],"the":[18,36,46,70,77,106,110,115,120,123,127,132],"Haar":[19],"cascade":[20],"classifier":[21],"was":[22,32,42,108,112,117,125,129,134],"to":[24,34,44,56,75],"find":[25],"candidate":[26,47],"regions.":[27],"Then,":[28],"DoG":[30],"filter":[31],"detect":[35],"edges":[37],"and":[38,63,69,92,100,114,131],"connected":[39],"component":[40],"labeling":[41],"applied":[43],"obtain":[45],"blocks.":[48],"The":[49,66,86],"color":[52,64],"characteristics":[53],"were":[54,73],"eliminate":[57],"irrelevant":[58],"blocks":[59],"using":[60],"histogram":[61],"comparison":[62],"quantization.":[65],"Bhattacharyya":[67],"distance":[68],"correlation":[71],"metric":[72],"compare":[76],"histograms.":[78],"Experiments":[79],"with":[80],"real":[81],"data":[82],"showed":[83],"good":[84],"performance.":[85],"dataset":[87],"consists":[88],"of":[89],"various":[90],"road":[91],"weather":[93],"conditions":[94],"including":[95],"expressway,":[96],"downtown,":[97],"sunny":[98],"days":[99],"rainy":[101],"days.":[102],"For":[103,119],"our":[104],"dataset,":[105,122],"recall":[107,124],"0.72,":[109],"precision":[111,128],"0.88":[113],"F-score":[116,133],"0.79.":[118],"Caltech":[121],"0.86,":[126],"0.96":[130],"0.91.":[135]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}