{"id":"https://openalex.org/W3080114534","doi":"https://doi.org/10.1142/s0219467821500121","title":"An Efficient Cooperative Smearing Technique for Degraded Historical Document Image Segmentation","display_name":"An Efficient Cooperative Smearing Technique for Degraded Historical Document Image Segmentation","publication_year":2020,"publication_date":"2020-08-25","ids":{"openalex":"https://openalex.org/W3080114534","doi":"https://doi.org/10.1142/s0219467821500121","mag":"3080114534"},"language":"en","primary_location":{"id":"doi:10.1142/s0219467821500121","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467821500121","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","raw_type":"journal-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/A5068428537","display_name":"Omar Boudraa","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Omar Boudraa","raw_affiliation_strings":["Laboratoire LCSI, \u00c9cole nationale Sup\u00e9rieure d\u2019Informatique, BP 68M, 16309, Oued-Smar Alger, Alg\u00e9rie"],"affiliations":[{"raw_affiliation_string":"Laboratoire LCSI, \u00c9cole nationale Sup\u00e9rieure d\u2019Informatique, BP 68M, 16309, Oued-Smar Alger, Alg\u00e9rie","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109557314","display_name":"Walid Khaled Hidouci","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Walid Khaled Hidouci","raw_affiliation_strings":["Laboratoire LCSI, \u00c9cole nationale Sup\u00e9rieure d\u2019Informatique, BP 68M, 16309, Oued-Smar Alger, Alg\u00e9rie"],"affiliations":[{"raw_affiliation_string":"Laboratoire LCSI, \u00c9cole nationale Sup\u00e9rieure d\u2019Informatique, BP 68M, 16309, Oued-Smar Alger, Alg\u00e9rie","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004426485","display_name":"Dominique Michelucci","orcid":"https://orcid.org/0000-0002-1256-9080"},"institutions":[{"id":"https://openalex.org/I177064439","display_name":"Universit\u00e9 de Bourgogne","ror":"https://ror.org/03k1bsr36","country_code":"FR","type":"education","lineage":["https://openalex.org/I177064439"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Dominique Michelucci","raw_affiliation_strings":["Laboratoire LIB, Universit\u00e9 de Bourgogne, BP 47870, 21078, DIJON CEDEX, France"],"affiliations":[{"raw_affiliation_string":"Laboratoire LIB, Universit\u00e9 de Bourgogne, BP 47870, 21078, DIJON CEDEX, France","institution_ids":["https://openalex.org/I177064439"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5068428537"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1954,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.49354709,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"21","issue":"02","first_page":"2150012","last_page":"2150012"},"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9961000084877014,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9937000274658203,"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/historical-document","display_name":"Historical document","score":0.7858677506446838},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.779063880443573},{"id":"https://openalex.org/keywords/document-layout-analysis","display_name":"Document layout analysis","score":0.7265121936798096},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.7199129462242126},{"id":"https://openalex.org/keywords/skew","display_name":"Skew","score":0.705586314201355},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6688333749771118},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6100651025772095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5835078954696655},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.47091981768608093},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4575464129447937},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4222675561904907},{"id":"https://openalex.org/keywords/optical-character-recognition","display_name":"Optical character recognition","score":0.41776248812675476},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3974176049232483},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3487898111343384}],"concepts":[{"id":"https://openalex.org/C2778371909","wikidata":"https://www.wikidata.org/wiki/Q3771738","display_name":"Historical document","level":2,"score":0.7858677506446838},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.779063880443573},{"id":"https://openalex.org/C72773152","wikidata":"https://www.wikidata.org/wiki/Q5287629","display_name":"Document layout analysis","level":3,"score":0.7265121936798096},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7199129462242126},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.705586314201355},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6688333749771118},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6100651025772095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5835078954696655},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.47091981768608093},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4575464129447937},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4222675561904907},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.41776248812675476},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3974176049232483},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3487898111343384},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1142/s0219467821500121","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467821500121","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","raw_type":"journal-article"},{"id":"pmh:oai:HAL:hal-03058799v1","is_oa":false,"landing_page_url":"https://hal.science/hal-03058799","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal of Image and Graphics, In press, &#x27E8;10.1142/S0219467821500121&#x27E9;","raw_type":"Journal articles"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1996512564","https://openalex.org/W2008109610","https://openalex.org/W2024077020","https://openalex.org/W2074138769","https://openalex.org/W2096497661","https://openalex.org/W2135164809","https://openalex.org/W2137982097","https://openalex.org/W2152372300","https://openalex.org/W2156730108","https://openalex.org/W2170472910","https://openalex.org/W2594443378","https://openalex.org/W2771577145","https://openalex.org/W2836275081","https://openalex.org/W2948918338"],"related_works":["https://openalex.org/W2559352488","https://openalex.org/W2964044735","https://openalex.org/W4300560548","https://openalex.org/W1969168333","https://openalex.org/W2131730163","https://openalex.org/W3046471831","https://openalex.org/W2051072213","https://openalex.org/W2784287639","https://openalex.org/W4294702218","https://openalex.org/W2119179626"],"abstract_inverted_index":{"Segmentation":[0],"is":[1,90],"one":[2],"of":[3,17,37,62,114],"the":[4,15,18,28,35,54,60,63,78,84,108,111,129],"critical":[5],"steps":[6],"in":[7,92,99,127],"historical":[8],"document":[9,64,121],"image":[10],"analysis":[11],"systems":[12],"that":[13,80],"determines":[14],"quality":[16,61],"search,":[19],"understanding,":[20],"recognition":[21],"and":[22,33,42,65,76,97,102,110,136],"interpretation":[23],"processes.":[24],"It":[25],"allows":[26],"isolating":[27],"objects":[29],"to":[30,58,66,82,94],"be":[31],"considered":[32],"separating":[34],"regions":[36],"interest":[38],"(paragraphs,":[39],"lines,":[40],"words":[41,96],"characters)":[43],"from":[44,70],"other":[45],"entities":[46],"(figures,":[47],"graphs,":[48],"tables,":[49],"etc.).":[50],"This":[51],"stage":[52],"follows":[53],"thresholding,":[55],"which":[56,128],"aims":[57],"improve":[59],"extract":[67],"its":[68,71],"background":[69],"foreground,":[72],"also":[73],"for":[74],"detecting":[75],"correcting":[77],"skew":[79],"leads":[81],"redress":[83],"document.":[85],"Here,":[86],"a":[87],"hybrid":[88],"method":[89],"proposed":[91],"order":[93],"locate":[95],"characters":[98],"both":[100],"handwritten":[101],"printed":[103],"documents.":[104],"Numerical":[105],"results":[106],"prove":[107],"robustness":[109],"high":[112],"precision":[113],"our":[115],"approach":[116],"applied":[117],"on":[118],"old":[119],"degraded":[120],"images":[122],"over":[123],"four":[124],"common":[125],"datasets,":[126],"pair":[130],"(Recall,":[131],"Precision)":[132],"reaches":[133],"approximately":[134],"97.7%":[135],"97.9%.":[137]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2020-09-01T00:00:00"}
