{"id":"https://openalex.org/W4214748977","doi":"https://doi.org/10.1587/transinf.2021edp7218","title":"Adaptive Binarization for Vehicle State Images Based on Contrast Preserving Decolorization and Major Cluster Estimation","display_name":"Adaptive Binarization for Vehicle State Images Based on Contrast Preserving Decolorization and Major Cluster Estimation","publication_year":2022,"publication_date":"2022-02-28","ids":{"openalex":"https://openalex.org/W4214748977","doi":"https://doi.org/10.1587/transinf.2021edp7218"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2021edp7218","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2021edp7218","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E105.D/3/E105.D_2021EDP7218/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/E105.D/3/E105.D_2021EDP7218/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089331963","display_name":"Ye Tian","orcid":"https://orcid.org/0000-0002-0981-6677"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ye TIAN","raw_affiliation_strings":["Data and Intelligence R&D Center, Zhuzhou CRRC Times Electric Co., Ltd"],"affiliations":[{"raw_affiliation_string":"Data and Intelligence R&D Center, Zhuzhou CRRC Times Electric Co., Ltd","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100774500","display_name":"Mei Han","orcid":"https://orcid.org/0000-0002-3123-2205"},"institutions":[{"id":"https://openalex.org/I49934816","display_name":"Hunan University of Technology","ror":"https://ror.org/04j3vr751","country_code":"CN","type":"education","lineage":["https://openalex.org/I49934816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mei HAN","raw_affiliation_strings":["School of Electrical and Information Engineering, Hunan University of Technology"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Hunan University of Technology","institution_ids":["https://openalex.org/I49934816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089331963"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.22,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52017654,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"E105.D","issue":"3","first_page":"679","last_page":"688"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9965999722480774,"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":0.9965999722480774,"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":0.9829000234603882,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9670000076293945,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/computer-science","display_name":"Computer science","score":0.7879226207733154},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6437829732894897},{"id":"https://openalex.org/keywords/otsus-method","display_name":"Otsu's method","score":0.6319370865821838},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.5921837091445923},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5300583243370056},{"id":"https://openalex.org/keywords/identifier","display_name":"Identifier","score":0.5214937925338745},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4833466708660126},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4701393246650696},{"id":"https://openalex.org/keywords/threshold-limit-value","display_name":"Threshold limit value","score":0.4490346908569336},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.44393303990364075},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.43295663595199585},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4243970811367035},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4216304421424866},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.41258862614631653},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.35901206731796265},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.35359668731689453},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3176591992378235},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15916132926940918},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0971727967262268}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7879226207733154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6437829732894897},{"id":"https://openalex.org/C21729346","wikidata":"https://www.wikidata.org/wiki/Q2444417","display_name":"Otsu's method","level":4,"score":0.6319370865821838},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.5921837091445923},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5300583243370056},{"id":"https://openalex.org/C154504017","wikidata":"https://www.wikidata.org/wiki/Q853614","display_name":"Identifier","level":2,"score":0.5214937925338745},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4833466708660126},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4701393246650696},{"id":"https://openalex.org/C64413873","wikidata":"https://www.wikidata.org/wiki/Q21005","display_name":"Threshold limit value","level":2,"score":0.4490346908569336},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.44393303990364075},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.43295663595199585},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4243970811367035},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4216304421424866},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.41258862614631653},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.35901206731796265},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.35359668731689453},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3176591992378235},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15916132926940918},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0971727967262268},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2021edp7218","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2021edp7218","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E105.D/3/E105.D_2021EDP7218/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2021edp7218","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2021edp7218","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E105.D/3/E105.D_2021EDP7218/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4214748977.pdf","grobid_xml":"https://content.openalex.org/works/W4214748977.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W283832546","https://openalex.org/W1915428456","https://openalex.org/W1965886316","https://openalex.org/W1973880112","https://openalex.org/W1977556410","https://openalex.org/W1979725976","https://openalex.org/W1998252428","https://openalex.org/W2052393437","https://openalex.org/W2081868602","https://openalex.org/W2090550165","https://openalex.org/W2128060444","https://openalex.org/W2133059825","https://openalex.org/W2511850448","https://openalex.org/W2570695987","https://openalex.org/W2751352153","https://openalex.org/W2755465093","https://openalex.org/W2887260487","https://openalex.org/W2969832672","https://openalex.org/W3013571015"],"related_works":["https://openalex.org/W2370610008","https://openalex.org/W27199137","https://openalex.org/W1979904741","https://openalex.org/W3150880786","https://openalex.org/W2085168425","https://openalex.org/W2387026783","https://openalex.org/W832910417","https://openalex.org/W2387401916","https://openalex.org/W2390133426","https://openalex.org/W2353730681"],"abstract_inverted_index":{"A":[0],"new":[1],"adaptive":[2,157],"binarization":[3,200],"method":[4,24,70,80,194,243],"is":[5,159,195],"proposed":[6,69],"for":[7,94,166,236],"the":[8,14,27,33,49,58,63,68,79,86,95,98,104,108,114,118,121,124,131,156,162,184,198,204,210,242,246,256],"vehicle":[9,29,50,109,145,185,268],"state":[10,110,146,186],"images":[11,111,147,187,265],"obtained":[12,149],"from":[13],"intelligent":[15,34,237],"operation":[16,35,51],"and":[17,36,44,47,56,92,116,123,134,155,173,209,222,250],"maintenance":[18,37],"system":[19,38],"of":[20,39,62,67,81,89,97,107,128,137,144,248,266],"rail":[21,40,238],"transit.":[22],"The":[23,65,178],"can":[25,102,169,244],"check":[26],"corresponding":[28,140],"status":[30,52],"information":[31,106,176],"in":[32,53],"transit":[41,239],"more":[42],"quickly":[43],"effectively,":[45],"track":[46],"monitor":[48],"real":[54],"time,":[55],"improve":[57,245],"emergency":[59],"response":[60],"ability":[61],"system.":[64],"advantages":[66],"mainly":[71],"include":[72],"two":[73],"points.":[74],"For":[75],"decolorization,":[76],"we":[77],"use":[78],"contrast":[82,119],"preserving":[83],"decolorization[1]":[84],"obtain":[85],"appropriate":[87],"ratio":[88],"R,":[90],"G,":[91],"B":[93],"grayscale":[96],"RGB":[99],"image":[100,233],"which":[101,168],"retain":[103],"color":[105,191],"background":[112,143,190],"to":[113,141],"maximum,":[115],"maintain":[117],"between":[120],"foreground":[122],"background.":[125],"In":[126],"terms":[127],"threshold":[129,158,206,212],"selection,":[130],"mean":[132],"value":[133,139],"standard":[135],"deviation":[136],"gray":[138],"multi-color":[142],"are":[148],"by":[150,161,254],"using":[151],"major":[152],"cluster":[153],"estimation[2],":[154],"determined":[160],"2":[163],"sigma":[164],"principle":[165],"binarization,":[167],"extract":[170],"text,":[171],"identifier":[172,251],"other":[174],"target":[175],"effectively.":[177],"experimental":[179],"results":[180],"show":[181],"that,":[182],"regarding":[183],"with":[188],"rich":[189],"information,":[192],"this":[193],"better":[196],"than":[197],"traditional":[199],"methods,":[201],"such":[202],"as":[203],"global":[205],"Otsu":[207],"algorithm[3]":[208],"local":[211],"Sauvola":[213],"algorithm[4],[5]":[214],"based":[215,227],"on":[216,228],"threshold,":[217],"Mean-Shift":[218],"algorithm[6],":[219],"K-Means":[220],"algorithm[7]":[221],"Fuzzy":[223],"C":[224],"Means[8]":[225],"algorithm":[226],"statistical":[229],"learning.":[230],"As":[231],"an":[232],"preprocessing":[234],"scheme":[235],"data":[240,262],"verification,":[241],"accuracy":[247],"text":[249],"recognition":[252,259],"effectively":[253],"verifying":[255],"optical":[257],"character":[258],"through":[260],"a":[261],"set":[263],"containing":[264],"different":[267],"statuses.":[269]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}