{"id":"https://openalex.org/W2033755059","doi":"https://doi.org/10.1142/s0218001410007889","title":"AN ADAPTIVE LAYER-BASED LOCAL BINARIZATION TECHNIQUE FOR DEGRADED DOCUMENTS","display_name":"AN ADAPTIVE LAYER-BASED LOCAL BINARIZATION TECHNIQUE FOR DEGRADED DOCUMENTS","publication_year":2010,"publication_date":"2010-03-01","ids":{"openalex":"https://openalex.org/W2033755059","doi":"https://doi.org/10.1142/s0218001410007889","mag":"2033755059"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001410007889","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001410007889","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"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 Pattern Recognition and Artificial Intelligence","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/A5015419644","display_name":"Michail Makridis","orcid":"https://orcid.org/0000-0001-7462-4674"},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"MICHAEL MAKRIDIS","raw_affiliation_strings":["Image Processing and Multimedia Laboratory, Department of Electrical &amp; Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing and Multimedia Laboratory, Department of Electrical &amp; Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece","institution_ids":["https://openalex.org/I147962203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110446833","display_name":"N. Papamarkos","orcid":null},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"N. PAPAMARKOS","raw_affiliation_strings":["Image Processing and Multimedia Laboratory, Department of Electrical &amp; Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing and Multimedia Laboratory, Department of Electrical &amp; Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece","institution_ids":["https://openalex.org/I147962203"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I147962203"],"apc_list":null,"apc_paid":null,"fwci":0.3174,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.58820096,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"24","issue":"02","first_page":"245","last_page":"279"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9980000257492065,"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":0.9973000288009644,"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/grayscale","display_name":"Grayscale","score":0.8425390720367432},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8048739433288574},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7946580648422241},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6957910060882568},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6454558372497559},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5928509831428528},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5798781514167786},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5538142323493958},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4617372453212738},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4541459083557129},{"id":"https://openalex.org/keywords/background-noise","display_name":"Background noise","score":0.4340030252933502},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4121650457382202},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15308445692062378}],"concepts":[{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.8425390720367432},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8048739433288574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7946580648422241},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6957910060882568},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6454558372497559},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5928509831428528},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5798781514167786},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5538142323493958},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4617372453212738},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4541459083557129},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.4340030252933502},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4121650457382202},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15308445692062378},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001410007889","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001410007889","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"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 Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1622620102","https://openalex.org/W1965117166","https://openalex.org/W1975153766","https://openalex.org/W2005515365","https://openalex.org/W2008748102","https://openalex.org/W2015230810","https://openalex.org/W2039269145","https://openalex.org/W2081826591","https://openalex.org/W2083970667","https://openalex.org/W2092564322","https://openalex.org/W2127319406","https://openalex.org/W2128060444","https://openalex.org/W2133059825","https://openalex.org/W2146402989","https://openalex.org/W2148539800","https://openalex.org/W2169249773","https://openalex.org/W4245402881","https://openalex.org/W4256052366"],"related_works":["https://openalex.org/W115686965","https://openalex.org/W2768918307","https://openalex.org/W2110031805","https://openalex.org/W2040020606","https://openalex.org/W4362659915","https://openalex.org/W2113071088","https://openalex.org/W2116526828","https://openalex.org/W2321543601","https://openalex.org/W1691631808","https://openalex.org/W1586320973"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,28,45,57,75,91],"new":[4,58,72,92],"technique":[5,15,116],"for":[6,36],"adaptive":[7],"binarization":[8,115,130],"of":[9,77,146],"degraded":[10,18],"document":[11,105],"images.":[12],"The":[13,102,113],"proposed":[14,114],"focuses":[16],"on":[17,121,137],"documents":[19,123],"with":[20,127],"various":[21],"background":[22,31,43,52,63,78,84],"patterns":[23],"and":[24,65,79,83,99,124,140],"noise.":[25],"It":[26],"involves":[27],"preprocessing":[29],"local":[30,67],"estimation":[32],"stage,":[33],"which":[34,94,134],"detects":[35],"each":[37],"pixel":[38],"that":[39],"is":[40,53,74,106],"considered":[41],"as":[42],"one,":[44],"proper":[46],"grayscale":[47,98],"value.":[48],"Then,":[49],"the":[50,71,144,147],"estimated":[51],"used":[54],"to":[55],"produce":[56],"enhanced":[59],"image":[60,73],"having":[61],"uniform":[62],"layers":[64,85],"increased":[66],"contrast.":[68],"That":[69],"is,":[70],"combination":[76],"foreground":[80,111],"layers.":[81,112],"Foreground":[82],"are":[86,135],"then":[87],"separated":[88],"by":[89,108],"using":[90],"transformation":[93],"exploits":[95],"efficiently,":[96],"both":[97],"spatial":[100],"information.":[101],"final":[103],"binary":[104],"obtained":[107],"combining":[109],"all":[110],"has":[117],"been":[118],"extensively":[119],"tested":[120],"numerous":[122],"successfully":[125],"compared":[126],"other":[128],"well-known":[129],"techniques.":[131],"Experimental":[132],"results,":[133],"based":[136],"statistical,":[138],"visual":[139],"OCR":[141],"criteria,":[142],"verify":[143],"effectiveness":[145],"technique.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
