{"id":"https://openalex.org/W2077896452","doi":"https://doi.org/10.1109/dicta.2012.6411703","title":"A New Method for Word Segmentation from Arbitrarily-Oriented Video Text Lines","display_name":"A New Method for Word Segmentation from Arbitrarily-Oriented Video Text Lines","publication_year":2012,"publication_date":"2012-12-01","ids":{"openalex":"https://openalex.org/W2077896452","doi":"https://doi.org/10.1109/dicta.2012.6411703","mag":"2077896452"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2012.6411703","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2012.6411703","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 International Conference on Digital Image Computing Techniques and Applications (DICTA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10072/51287","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008754736","display_name":"Nabin Sharma","orcid":"https://orcid.org/0000-0003-0841-1245"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Nabin Sharma","raw_affiliation_strings":["Griffith University, Queensland, Australia","Griffith Univ., Griffith, QLD, Australia"],"affiliations":[{"raw_affiliation_string":"Griffith University, Queensland, Australia","institution_ids":["https://openalex.org/I11701301"]},{"raw_affiliation_string":"Griffith Univ., Griffith, QLD, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025871978","display_name":"Palaiahnakote Shivakumara","orcid":"https://orcid.org/0000-0001-9026-4613"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Palaiahnakote Shivakumara","raw_affiliation_strings":["School of Computing, National University of Singapore, Singapore","Sch. of Comput. Nat., Univ. of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computing, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"Sch. of Comput. Nat., Univ. of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068803496","display_name":"Umapada Pal","orcid":"https://orcid.org/0000-0002-5426-2618"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Umapada Pal","raw_affiliation_strings":["Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, India","Comput. Vision & Pattern Recognition Unit, Indian Stat. Inst., Kolkata, India#TAB#"],"affiliations":[{"raw_affiliation_string":"Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]},{"raw_affiliation_string":"Comput. Vision & Pattern Recognition Unit, Indian Stat. Inst., Kolkata, India#TAB#","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045600512","display_name":"Michael Blumenstein","orcid":"https://orcid.org/0000-0002-9908-3744"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Michael Blumenstein","raw_affiliation_strings":["Griffith University, Queensland, Australia","Griffith Univ., Griffith, QLD, Australia"],"affiliations":[{"raw_affiliation_string":"Griffith University, Queensland, Australia","institution_ids":["https://openalex.org/I11701301"]},{"raw_affiliation_string":"Griffith Univ., Griffith, QLD, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111664929","display_name":"Chew Lim Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chew Lim Tan","raw_affiliation_strings":["School of Computing, National University of Singapore, Singapore","Sch. of Comput. Nat., Univ. of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computing, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"Sch. of Comput. Nat., Univ. of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5008754736"],"corresponding_institution_ids":["https://openalex.org/I11701301"],"apc_list":null,"apc_paid":null,"fwci":2.4981,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.90653426,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9998999834060669,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9969000220298767,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9962000250816345,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6983288526535034},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6718802452087402},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.664330244064331},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.6336119771003723},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6009133458137512},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5888867974281311},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.5701270699501038},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5581555366516113},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5490678548812866},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.522536039352417},{"id":"https://openalex.org/keywords/connected-component","display_name":"Connected component","score":0.4917769730091095},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4125368595123291},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22977498173713684},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.1118851900100708}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6983288526535034},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6718802452087402},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.664330244064331},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.6336119771003723},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6009133458137512},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5888867974281311},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.5701270699501038},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5581555366516113},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5490678548812866},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.522536039352417},{"id":"https://openalex.org/C193435613","wikidata":"https://www.wikidata.org/wiki/Q2997928","display_name":"Connected component","level":2,"score":0.4917769730091095},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4125368595123291},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22977498173713684},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1118851900100708}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/dicta.2012.6411703","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2012.6411703","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 International Conference on Digital Image Computing Techniques and Applications (DICTA)","raw_type":"proceedings-article"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/51287","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/51287","pdf_url":"http://hdl.handle.net/10072/51287","source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/42112","is_oa":false,"landing_page_url":"http://scholarbank.nus.edu.sg/handle/10635/42112","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus","raw_type":"Conference Paper"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.301.7599","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.7599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.comp.nus.edu.sg/~tancl/publications/c2012/DICTA_PID1141978.pdf","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:research-repository.griffith.edu.au:10072/51287","is_oa":true,"landing_page_url":"http://hdl.handle.net/10072/51287","pdf_url":"http://hdl.handle.net/10072/51287","source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"},"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320981","display_name":"Griffith University","ror":"https://ror.org/02sc3r913"},{"id":"https://openalex.org/F4320327938","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2077896452.pdf"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W195934188","https://openalex.org/W1996257677","https://openalex.org/W2005402843","https://openalex.org/W2014286161","https://openalex.org/W2027883219","https://openalex.org/W2043011136","https://openalex.org/W2064245055","https://openalex.org/W2065350108","https://openalex.org/W2081868602","https://openalex.org/W2099063119","https://openalex.org/W2099306567","https://openalex.org/W2104633387","https://openalex.org/W2110315813","https://openalex.org/W2123827229","https://openalex.org/W2130475102","https://openalex.org/W2134378185","https://openalex.org/W2158610162","https://openalex.org/W2165569569","https://openalex.org/W2169680646","https://openalex.org/W6667094255","https://openalex.org/W6685083972"],"related_works":["https://openalex.org/W2393940967","https://openalex.org/W2159591557","https://openalex.org/W2385598138","https://openalex.org/W2366925922","https://openalex.org/W2346578824","https://openalex.org/W2905950556","https://openalex.org/W2112534334","https://openalex.org/W2115592387","https://openalex.org/W120168696","https://openalex.org/W2153245103"],"abstract_inverted_index":{"Word":[0],"segmentation":[1,32],"has":[2],"become":[3],"a":[4,16,77,105,233],"research":[5],"topic":[6],"to":[7,59,75,92,127,150,165,180,200],"improve":[8],"OCR":[9],"accuracy":[10],"for":[11,30,48,108,115,154],"video":[12,17,35,212],"text":[13,18,36,56,78,88,94,214,223],"recognition,":[14],"because":[15],"line":[19,57,95],"suffers":[20],"from":[21,33,225],"arbitrary":[22],"orientation,":[23],"complex":[24],"background":[25],"and":[26,131,144,161,184,195,222,232,241],"low":[27],"resolution.":[28],"Therefore,":[29],"word":[31,130,142,183,204],"arbitrarily-oriented":[34],"lines,":[37,215,218],"in":[38,86],"this":[39],"paper,":[40],"we":[41,103,121],"extract":[42],"four":[43,61,69],"new":[44],"gradient":[45],"directional":[46],"features":[47],"each":[49,159],"Canny":[50],"edge":[51],"pixel":[52,63,70],"of":[53,68,83,197],"the":[54,84,87,93,112,116,119,151,166,169,173,176,189,198,202,226,237],"input":[55],"image":[58,90],"produce":[60],"respective":[62],"candidate":[64,71,79,89],"images.":[65],"The":[66,81,135,206],"union":[67],"images":[72],"is":[73,96,208],"performed":[74],"obtain":[76],"image.":[80],"sequence":[82],"components":[85,147,199],"according":[91],"determined":[97],"using":[98],"nearest":[99],"neighbor":[100],"criteria.":[101],"Then":[102,188],"propose":[104],"two-stage":[106],"method":[107,170,190,207],"segmenting":[109,155],"words.":[110,157],"In":[111],"first":[113],"stage,":[114,168],"distances":[117],"between":[118],"components,":[120],"apply":[122],"K-means":[123,177],"clustering":[124,178],"with":[125],"K=2":[126],"get":[128],"probable":[129,141,182],"non-word":[132,185],"spacing":[133,143,186],"clusters.":[134,187],"words":[136,163],"are":[137,148,239],"segmented":[138,160],"based":[139],"on":[140,211],"all":[145,172],"other":[146],"passed":[149,164],"second":[152,167],"stage":[153],"correct":[156,203],"For":[158],"un-segmented":[162],"repeats":[171],"steps":[174],"until":[175],"step":[179],"find":[181],"considers":[191],"cluster":[192],"nature,":[193],"height":[194],"width":[196],"identify":[201],"spacing.":[205],"tested":[209],"extensively":[210],"curved":[213],"non-horizontal":[216],"straight":[217,220],"horizontal":[219],"lines":[221,224],"ICDAR-2003":[227],"competition":[228],"data.":[229],"Experimental":[230],"results":[231,238],"comparative":[234],"study":[235],"shows":[236],"encouraging":[240],"promising.":[242]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}