{"id":"https://openalex.org/W2038677313","doi":"https://doi.org/10.1117/12.2008338","title":"Local projection-based character segmentation method for historical Chinese documents","display_name":"Local projection-based character segmentation method for historical Chinese documents","publication_year":2013,"publication_date":"2013-02-04","ids":{"openalex":"https://openalex.org/W2038677313","doi":"https://doi.org/10.1117/12.2008338","mag":"2038677313"},"language":"en","primary_location":{"id":"doi:10.1117/12.2008338","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2008338","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5042544148","display_name":"Linjie Yang","orcid":"https://orcid.org/0000-0003-2766-1143"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Linjie Yang","raw_affiliation_strings":["Tsinghua Univ. (China)","#N##TAB##TAB##TAB##TAB# Tsinghua University, China#N##TAB##TAB##TAB#"],"affiliations":[{"raw_affiliation_string":"Tsinghua Univ. (China)","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"#N##TAB##TAB##TAB##TAB# Tsinghua University, China#N##TAB##TAB##TAB#","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076442506","display_name":"Liangrui Peng","orcid":"https://orcid.org/0000-0001-7793-1039"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangrui Peng","raw_affiliation_strings":["Tsinghua Univ. (China)","#N##TAB##TAB##TAB##TAB# Tsinghua University, China#N##TAB##TAB##TAB#"],"affiliations":[{"raw_affiliation_string":"Tsinghua Univ. (China)","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"#N##TAB##TAB##TAB##TAB# Tsinghua University, China#N##TAB##TAB##TAB#","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5042544148"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.5443,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70068195,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"8658","issue":null,"first_page":"86580O","last_page":"86580O"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9954000115394592,"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":0.9954000115394592,"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":0.9864000082015991,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9620000123977661,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7813230752944946},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.7573897838592529},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7386263608932495},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6442395448684692},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6290598511695862},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.601806104183197},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5894717574119568},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5664862990379333},{"id":"https://openalex.org/keywords/optical-character-recognition","display_name":"Optical character recognition","score":0.555212676525116},{"id":"https://openalex.org/keywords/digitization","display_name":"Digitization","score":0.5077496767044067},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4888100326061249},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.45949697494506836},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.4421052932739258},{"id":"https://openalex.org/keywords/chinese-characters","display_name":"Chinese characters","score":0.4247901439666748},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40310990810394287},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14871057868003845}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7813230752944946},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.7573897838592529},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7386263608932495},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6442395448684692},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6290598511695862},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.601806104183197},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5894717574119568},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5664862990379333},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.555212676525116},{"id":"https://openalex.org/C2779308522","wikidata":"https://www.wikidata.org/wiki/Q843958","display_name":"Digitization","level":2,"score":0.5077496767044067},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4888100326061249},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.45949697494506836},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.4421052932739258},{"id":"https://openalex.org/C2781051154","wikidata":"https://www.wikidata.org/wiki/Q8201","display_name":"Chinese characters","level":2,"score":0.4247901439666748},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40310990810394287},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14871057868003845},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2008338","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2008338","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2185902295","https://openalex.org/W2945274617","https://openalex.org/W2372421320","https://openalex.org/W2057775483","https://openalex.org/W2041871225","https://openalex.org/W2386644571","https://openalex.org/W4205800335","https://openalex.org/W2387793296","https://openalex.org/W1558398159"],"abstract_inverted_index":{"Digitization":[0],"of":[1,53,69,91,106,116],"historical":[2,36],"Chinese":[3,37],"documents":[4],"includes":[5],"two":[6],"key":[7],"technologies,":[8],"character":[9,12,19,44,92],"segmentation":[10,20,45,96],"and":[11,73,98,101],"recognition.":[13],"This":[14],"paper":[15],"focuses":[16],"on":[17,51,88,108],"developing":[18],"algorithm.":[21,119],"As":[22],"a":[23,35,42,54,74,103,109],"preprocessing":[24],"step,":[25],"we":[26],"combine":[27],"several":[28],"effective":[29],"measures":[30],"to":[31],"remove":[32],"noises":[33],"in":[34,57],"document":[38],"image.":[39,81],"After":[40],"binarization,":[41],"new":[43],"algorithm":[46,86],"segment":[47],"single":[48],"characters":[49],"based":[50,87],"projections":[52],"cost":[55,61],"image":[56,62,76],"local":[58],"windows.":[59],"The":[60],"is":[63],"constructed":[64],"by":[65],"utilizing":[66],"the":[67,79,84,114,117],"information":[68],"stroke":[70],"bounding":[71,93],"boxes":[72,94],"skeleton":[75],"extracted":[77],"from":[78],"binarized":[80],"We":[82],"evaluate":[83],"proposed":[85,118],"matching":[89],"degrees":[90],"between":[95],"results":[97],"ground-truth":[99],"data,":[100],"achieve":[102],"recall":[104],"rate":[105],"74.3%":[107],"test":[110],"set,":[111],"which":[112],"shows":[113],"effectiveness":[115]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
