{"id":"https://openalex.org/W2089810362","doi":"https://doi.org/10.1109/icves.2013.6619599","title":"A vision-based serial number recognition algorithm for HSR trains by nearest neighbor chains of connected components","display_name":"A vision-based serial number recognition algorithm for HSR trains by nearest neighbor chains of connected components","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2089810362","doi":"https://doi.org/10.1109/icves.2013.6619599","mag":"2089810362"},"language":"en","primary_location":{"id":"doi:10.1109/icves.2013.6619599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves.2013.6619599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of 2013 IEEE International Conference on Vehicular Electronics and Safety","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/A5046508099","display_name":"Bo Li","orcid":"https://orcid.org/0000-0002-1415-4444"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Li","raw_affiliation_strings":["The State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing, China","State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]},{"raw_affiliation_string":"State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112113074","display_name":"Bin Tian","orcid":"https://orcid.org/0000-0003-1050-1282"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Tian","raw_affiliation_strings":["The State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing, China","State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]},{"raw_affiliation_string":"State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100339216","display_name":"Ye Li","orcid":"https://orcid.org/0000-0002-2898-5345"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Li","raw_affiliation_strings":["The State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing, China","State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]},{"raw_affiliation_string":"State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088979194","display_name":"Gang Xiong","orcid":"https://orcid.org/0000-0002-4303-5559"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Xiong","raw_affiliation_strings":["Institute of Automation Chinese Academy of Sciences, Beijing, Beijing, CN","State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation Chinese Academy of Sciences, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042359485","display_name":"Fenghua Zhu","orcid":"https://orcid.org/0000-0003-2886-6968"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fenghua Zhu","raw_affiliation_strings":["Institute of Automation Chinese Academy of Sciences, Beijing, Beijing, CN","State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation Chinese Academy of Sciences, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"37","issue":null,"first_page":"36","last_page":"41"},"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":0.9894999861717224,"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":0.9776999950408936,"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/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.7412436008453369},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7359462380409241},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.696307897567749},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.641012966632843},{"id":"https://openalex.org/keywords/connected-component","display_name":"Connected component","score":0.6302781105041504},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5752156972885132},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5735258460044861},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5373495817184448},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.5173091888427734},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5070650577545166},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48284822702407837},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.47039851546287537},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.44582003355026245},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4345414340496063},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3987473249435425},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1815352439880371}],"concepts":[{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.7412436008453369},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7359462380409241},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.696307897567749},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.641012966632843},{"id":"https://openalex.org/C193435613","wikidata":"https://www.wikidata.org/wiki/Q2997928","display_name":"Connected component","level":2,"score":0.6302781105041504},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5752156972885132},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5735258460044861},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5373495817184448},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.5173091888427734},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5070650577545166},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48284822702407837},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.47039851546287537},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.44582003355026245},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4345414340496063},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3987473249435425},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1815352439880371},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icves.2013.6619599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves.2013.6619599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of 2013 IEEE International Conference on Vehicular Electronics and Safety","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1964741520","https://openalex.org/W1975399404","https://openalex.org/W1980911747","https://openalex.org/W2019019933","https://openalex.org/W2022371268","https://openalex.org/W2078997308","https://openalex.org/W2104344166","https://openalex.org/W2110625202","https://openalex.org/W2112438422","https://openalex.org/W2120820227","https://openalex.org/W2135255579","https://openalex.org/W2161969291","https://openalex.org/W2169493540","https://openalex.org/W2387567027","https://openalex.org/W6641164337","https://openalex.org/W6680073459","https://openalex.org/W6684940549","https://openalex.org/W7067098502"],"related_works":["https://openalex.org/W2148008870","https://openalex.org/W2381195555","https://openalex.org/W4246757943","https://openalex.org/W2368606575","https://openalex.org/W2132753198","https://openalex.org/W2369874856","https://openalex.org/W2182477562","https://openalex.org/W2792185758","https://openalex.org/W2787484455","https://openalex.org/W2119808169"],"abstract_inverted_index":{"With":[0],"the":[1,48,60,67,72,100,110,118,124,136,151,159,173],"rapid":[2],"development":[3],"of":[4,21,51,64,79,117,142,177],"High":[5],"Speed":[6],"Railway":[7],"(HSR)":[8],"in":[9,32,71],"recent":[10],"years,":[11],"its":[12],"research":[13],"become":[14],"one":[15],"hot":[16],"academic":[17],"topic.":[18],"Serial":[19],"numbers":[20,50],"HSR":[22,52],"trains":[23,53],"are":[24,74,138,163],"unique":[25],"identifications,":[26],"which":[27,162],"play":[28],"an":[29],"important":[30],"role":[31],"railway":[33],"management":[34],"and":[35,146,175],"operation.":[36],"In":[37,150],"this":[38],"paper,":[39],"we":[40],"present":[41],"a":[42,77],"vision-based":[43],"algorithm":[44],"to":[45,59,90],"automatically":[46],"recognize":[47],"serial":[49,65,68,119,179],"by":[54,76,158],"image":[55,73],"sensors.":[56],"Firstly,":[57],"according":[58],"fixed":[61],"character":[62,129],"layout":[63],"numbers,":[66],"number":[69,120,180],"regions":[70],"located":[75],"combination":[78],"connected":[80,93,107],"components.":[81],"Maximally":[82],"Stable":[83],"Extremal":[84],"Region":[85],"(MSER)":[86],"detector":[87],"is":[88,121,156],"introduced":[89],"extract":[91],"reliable":[92],"components":[94,108],"as":[95],"candidate":[96],"characters.":[97],"Based":[98],"on":[99],"pairwise":[101],"geometry":[102],"relation":[103],"between":[104],"candidates,":[105],"these":[106],"constitute":[109],"nearest":[111,125],"neighbor":[112,126],"chain.":[113,127],"The":[114,169],"accurate":[115],"location":[116],"obtained":[122],"with":[123,140],"Meanwhile,":[128],"images":[130,161],"can":[131],"be":[132],"segmented":[133],"simultaneously.":[134],"Finally,":[135],"characters":[137],"recognized":[139],"Histogram":[141],"Gradient":[143],"(HoG)":[144],"features":[145],"simple":[147],"similarity-based":[148],"classifiers.":[149],"experiments,":[152],"our":[153,178],"recognition":[154,181],"performance":[155],"evaluated":[157],"test":[160],"collected":[164],"from":[165],"real":[166],"application":[167],"scenes.":[168],"experimental":[170],"results":[171],"show":[172],"reliability":[174],"effectiveness":[176],"algorithm.":[182]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}