{"id":"https://openalex.org/W2331889030","doi":"https://doi.org/10.1145/2809544.2809552","title":"Layout Analysis Algorithm Based on Probabilistic Graphical Model for Dunhuang Historical Documents","display_name":"Layout Analysis Algorithm Based on Probabilistic Graphical Model for Dunhuang Historical Documents","publication_year":2015,"publication_date":"2015-08-22","ids":{"openalex":"https://openalex.org/W2331889030","doi":"https://doi.org/10.1145/2809544.2809552","mag":"2331889030"},"language":"en","primary_location":{"id":"doi:10.1145/2809544.2809552","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2809544.2809552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Workshop on Historical Document Imaging and Processing","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/A5047872909","display_name":"Boqiang Fan","orcid":"https://orcid.org/0000-0002-4099-0155"},"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":"Boqiang Fan","raw_affiliation_strings":["Tsinghua National Laboratory for Information Science and Technology, Dept. of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua National Laboratory for Information Science and Technology, Dept. of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","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 National Laboratory for Information Science and Technology, Dept. of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua National Laboratory for Information Science and Technology, Dept. of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103455376","display_name":"Franck Lebourgeois","orcid":null},"institutions":[{"id":"https://openalex.org/I100532134","display_name":"Universit\u00e9 Claude Bernard Lyon 1","ror":"https://ror.org/029brtt94","country_code":"FR","type":"education","lineage":["https://openalex.org/I100532134","https://openalex.org/I203339264"]},{"id":"https://openalex.org/I4210155607","display_name":"Laboratoire d'Informatique en Images et Syst\u00e8mes d'Information","ror":"https://ror.org/04dv4he91","country_code":"FR","type":"facility","lineage":["https://openalex.org/I100532134","https://openalex.org/I112936343","https://openalex.org/I1294671590","https://openalex.org/I188626449","https://openalex.org/I203339264","https://openalex.org/I203339264","https://openalex.org/I203339264","https://openalex.org/I203339264","https://openalex.org/I4210155607","https://openalex.org/I48430043"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Franck Lebourgeois","raw_affiliation_strings":["LIRIS, Universit\u00e9 de Lyon, France"],"affiliations":[{"raw_affiliation_string":"LIRIS, Universit\u00e9 de Lyon, France","institution_ids":["https://openalex.org/I4210155607","https://openalex.org/I100532134"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5047872909"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17779974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"63","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.996399998664856,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.996399998664856,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9951000213623047,"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":0.9904999732971191,"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/computer-science","display_name":"Computer science","score":0.7500896453857422},{"id":"https://openalex.org/keywords/historical-document","display_name":"Historical document","score":0.6334793567657471},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.606979489326477},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5593899488449097},{"id":"https://openalex.org/keywords/document-layout-analysis","display_name":"Document layout analysis","score":0.4585660696029663},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.44590485095977783},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.438217431306839},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4373432993888855},{"id":"https://openalex.org/keywords/column","display_name":"Column (typography)","score":0.4354192018508911},{"id":"https://openalex.org/keywords/connected-component","display_name":"Connected component","score":0.43145108222961426},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4235711991786957},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.4213930070400238},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.413968026638031},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4011635184288025},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.26106059551239014}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7500896453857422},{"id":"https://openalex.org/C2778371909","wikidata":"https://www.wikidata.org/wiki/Q3771738","display_name":"Historical document","level":2,"score":0.6334793567657471},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.606979489326477},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5593899488449097},{"id":"https://openalex.org/C72773152","wikidata":"https://www.wikidata.org/wiki/Q5287629","display_name":"Document layout analysis","level":3,"score":0.4585660696029663},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.44590485095977783},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.438217431306839},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4373432993888855},{"id":"https://openalex.org/C2780551164","wikidata":"https://www.wikidata.org/wiki/Q2306599","display_name":"Column (typography)","level":3,"score":0.4354192018508911},{"id":"https://openalex.org/C193435613","wikidata":"https://www.wikidata.org/wiki/Q2997928","display_name":"Connected component","level":2,"score":0.43145108222961426},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4235711991786957},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.4213930070400238},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.413968026638031},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4011635184288025},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26106059551239014},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2809544.2809552","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2809544.2809552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Workshop on Historical Document Imaging and Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W8079469","https://openalex.org/W1973804542","https://openalex.org/W1993171301","https://openalex.org/W2006416652","https://openalex.org/W2015432638","https://openalex.org/W2016275632","https://openalex.org/W2019353007","https://openalex.org/W2020719504","https://openalex.org/W2026405299","https://openalex.org/W2058063932","https://openalex.org/W2063476404","https://openalex.org/W2064059121","https://openalex.org/W2100125468","https://openalex.org/W2112852975","https://openalex.org/W2114504958","https://openalex.org/W2118030626","https://openalex.org/W2135085165","https://openalex.org/W2154765787","https://openalex.org/W2749191161","https://openalex.org/W4248839592"],"related_works":["https://openalex.org/W2130283001","https://openalex.org/W2786527349","https://openalex.org/W3080114534","https://openalex.org/W2384880948","https://openalex.org/W39451508","https://openalex.org/W2898666172","https://openalex.org/W1988371238","https://openalex.org/W4367292478","https://openalex.org/W2093712129","https://openalex.org/W2934170162"],"abstract_inverted_index":{"The":[0,144,193,205],"Dunhuang":[1,45,170],"historical":[2,29,36,42,104,171,202,220],"documents":[3,30,43,62],"are":[4,46,63,107],"of":[5,11,28,60,186,191],"great":[6],"significance":[7],"to":[8,51,72,76,122,160,218],"the":[9,23,26,56,102,115,128,147,174,209],"study":[10,27],"ancient":[12],"Chinese":[13],"Buddhist":[14],"culture":[15],"and":[16,25,48,50,58,98,113,156,173,188],"other":[17],"topics.":[18],"It":[19],"would":[20],"greatly":[21],"benefit":[22],"protection":[24],"with":[31,182],"full-text":[32],"information":[33,121],"generated":[34],"by":[35,109],"document":[37,105,203,221],"recognition":[38],"technology.":[39],"However,":[40],"many":[41],"from":[44],"old":[47],"broken,":[49],"make":[52],"it":[53],"more":[54],"challenging,":[55],"style":[57],"layout":[59,68,84,211],"these":[61,77],"casual":[64],"as":[65],"well.":[66],"Traditional":[67],"analysis":[69,85,135,212],"algorithm":[70,86,136,213],"failed":[71],"pay":[73],"much":[74],"attention":[75],"problems.":[78],"In":[79,127],"this":[80],"paper,":[81],"a":[82,132,183],"new":[83],"based":[87,137,151],"on":[88,138,152,168],"Probabilistic":[89,139],"Graphical":[90,140],"Model":[91,141],"is":[92,142],"proposed,":[93],"including":[94],"both":[95],"rough":[96,116,124],"segmentation":[97,117,130],"fine":[99,129],"segmentation.":[100],"After":[101],"input":[103],"images":[106],"pre-processed":[108],"Gaussian":[110],"smoothed":[111],"filtering":[112],"binarization,":[114],"step":[118],"uses":[119],"projection":[120],"get":[123,161],"text-column":[125,195],"regions.":[126],"step,":[131],"connected":[133,149,158],"component":[134],"developed.":[143],"method":[145,176],"models":[146],"extracted":[148],"components":[150,159],"Markov":[153],"Random":[154],"Field,":[155],"combines":[157],"output":[162],"text":[163,180],"columns.":[164],"Experiments":[165],"were":[166],"conducted":[167],"some":[169],"documents,":[172],"proposed":[175,210],"could":[177,197,214],"correctly":[178],"segment":[179],"columns":[181],"recall":[184],"rate":[185],"90.0%":[187],"an":[189],"accuracy":[190],"77.7%.":[192],"segmented":[194],"regions":[196],"cover":[198],"99.2%":[199],"characters":[200],"in":[201],"images.":[204,222],"result":[206],"shows":[207],"that":[208],"be":[215],"successfully":[216],"applied":[217],"degraded":[219]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
