{"id":"https://openalex.org/W7162990095","doi":"https://doi.org/10.3390/make8060149","title":"Document Image Binarization Using Various Machine Learning Models and Ensembles Trained on Classic Local and Global Binarization Algorithms and Image Statistics","display_name":"Document Image Binarization Using Various Machine Learning Models and Ensembles Trained on Classic Local and Global Binarization Algorithms and Image Statistics","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7162990095","doi":"https://doi.org/10.3390/make8060149"},"language":"en","primary_location":{"id":"doi:10.3390/make8060149","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8060149","pdf_url":null,"source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/make8060149","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087013215","display_name":"Nicolae Tarb\u0103","orcid":"https://orcid.org/0000-0002-7769-8289"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Nicolae Tarb\u0103","raw_affiliation_strings":["Faculty of Automatic Control and Computers, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania"],"raw_orcid":"https://orcid.org/0000-0002-7769-8289","affiliations":[{"raw_affiliation_string":"Faculty of Automatic Control and Computers, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031177491","display_name":"Costin-Anton Boiangiu","orcid":"https://orcid.org/0000-0002-2987-4022"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Costin-Anton Boiangiu","raw_affiliation_strings":["Faculty of Automatic Control and Computers, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania"],"raw_orcid":"https://orcid.org/0000-0002-2987-4022","affiliations":[{"raw_affiliation_string":"Faculty of Automatic Control and Computers, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000795402","display_name":"Mihai-Lucian Voncil\u0103","orcid":"https://orcid.org/0000-0002-6764-9125"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Mihai-Lucian Voncil\u0103","raw_affiliation_strings":["Faculty of Automatic Control and Computers, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania"],"raw_orcid":"https://orcid.org/0000-0002-6764-9125","affiliations":[{"raw_affiliation_string":"Faculty of Automatic Control and Computers, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania","institution_ids":["https://openalex.org/I61641377"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I61641377"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1559},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1559},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68199909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"6","first_page":"149","last_page":"149"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.8162000179290771,"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":0.8162000179290771,"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":0.09549999982118607,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.010099999606609344,"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/thresholding","display_name":"Thresholding","score":0.8912000060081482},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7087000012397766},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6520000100135803},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.6126000285148621},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5891000032424927},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5314000248908997},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5163000226020813}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.8912000060081482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.777999997138977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7095000147819519},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7087000012397766},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6520000100135803},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.6126000285148621},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5891000032424927},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5314000248908997},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5163000226020813},{"id":"https://openalex.org/C2779308522","wikidata":"https://www.wikidata.org/wiki/Q843958","display_name":"Digitization","level":2,"score":0.5065000057220459},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44679999351501465},{"id":"https://openalex.org/C42781572","wikidata":"https://www.wikidata.org/wiki/Q1250322","display_name":"Digital image","level":4,"score":0.37139999866485596},{"id":"https://openalex.org/C202577368","wikidata":"https://www.wikidata.org/wiki/Q2576067","display_name":"Balanced histogram thresholding","level":5,"score":0.37119999527931213},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.36730000376701355},{"id":"https://openalex.org/C193828747","wikidata":"https://www.wikidata.org/wiki/Q864118","display_name":"Binary image","level":4,"score":0.32100000977516174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3109999895095825},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2922999858856201},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.251800000667572},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.25060001015663147}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make8060149","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8060149","pdf_url":null,"source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e20c804a93014ac8ae44355448fad99a","is_oa":false,"landing_page_url":"https://doaj.org/article/e20c804a93014ac8ae44355448fad99a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"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":"Machine Learning and Knowledge Extraction, Vol 8, Iss 6, p 149 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/make8060149","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8060149","pdf_url":null,"source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320329445","display_name":"Universitatea Politehnica din Bucure\u0219ti","ror":"https://ror.org/0558j5q12"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1975262195","https://openalex.org/W1991927948","https://openalex.org/W2009667652","https://openalex.org/W2016829658","https://openalex.org/W2053896220","https://openalex.org/W2065350108","https://openalex.org/W2066350139","https://openalex.org/W2071516577","https://openalex.org/W2072610689","https://openalex.org/W2091863778","https://openalex.org/W2128060444","https://openalex.org/W2133059825","https://openalex.org/W2156508493","https://openalex.org/W2157414682","https://openalex.org/W2170472910","https://openalex.org/W2577429903","https://openalex.org/W2759766068","https://openalex.org/W2785874433","https://openalex.org/W2911064732","https://openalex.org/W2911964244","https://openalex.org/W2915106267","https://openalex.org/W2915527102","https://openalex.org/W2922522433","https://openalex.org/W2957223244","https://openalex.org/W3003176962","https://openalex.org/W3003420173","https://openalex.org/W3010573836","https://openalex.org/W3035990434","https://openalex.org/W3083907077","https://openalex.org/W3146796711","https://openalex.org/W3157156894","https://openalex.org/W3209173547","https://openalex.org/W4220677852","https://openalex.org/W4241075495","https://openalex.org/W4243521730","https://openalex.org/W4246411305","https://openalex.org/W4247264488","https://openalex.org/W4248083651","https://openalex.org/W4281399251","https://openalex.org/W4311459452","https://openalex.org/W4385595249","https://openalex.org/W4386606149","https://openalex.org/W4387076916","https://openalex.org/W4388594412","https://openalex.org/W4390729184","https://openalex.org/W4391094496","https://openalex.org/W4406107089","https://openalex.org/W4409557490","https://openalex.org/W4412519598","https://openalex.org/W4412700289","https://openalex.org/W4413279258","https://openalex.org/W7127450507","https://openalex.org/W7134037248","https://openalex.org/W7134196174"],"related_works":[],"abstract_inverted_index":{"Image":[0],"binarization":[1,39,200],"is":[2,19,35,60],"a":[3,36,55,142],"preprocessing":[4],"technique":[5,40],"that":[6,147,176],"maps":[7],"an":[8],"image\u2019s":[9],"pixel":[10,47,97],"values":[11,48],"to":[12,81,133,155,174],"either":[13],"black":[14],"or":[15,52],"white,":[16],"and":[17,31,167,182],"it":[18,45,63,73,91,104,112],"crucial":[20],"in":[21,116],"many":[22,76],"fields":[23],"of":[24,78,109,119,137,163],"computer":[25],"vision,":[26],"such":[27,107],"as":[28],"document":[29,82,198],"digitization":[30],"medical":[32],"imaging.":[33],"Thresholding":[34],"popular":[37,150,197],"image":[38,169,199],"for":[41,68,95],"grayscale":[42],"images":[43],"because":[44,62,90],"splits":[46],"into":[49],"greater":[50,87],"than":[51,54],"lower":[53],"specific":[56,80],"threshold.":[57],"Global":[58],"thresholding":[59,85,145,165],"fast":[61],"computes":[64],"only":[65],"one":[66],"threshold":[67],"the":[69,93,100,120,161,177],"entire":[70],"image,":[71],"but":[72,103],"cannot":[74],"handle":[75,106,134],"types":[77,108,136],"noise":[79,115],"images.":[83],"Local":[84],"has":[86],"computational":[88],"complexity":[89],"adjusts":[92],"thresholds":[94],"each":[96],"based":[98],"on":[99,185,196],"surrounding":[101],"pixels,":[102],"can":[105,125],"noise,":[110],"although":[111],"risks":[113],"introducing":[114],"uniform":[117],"areas":[118],"image.":[121],"Mixed":[122],"global\u2013local":[123,144],"approaches":[124],"mitigate":[126],"this":[127],"risk":[128],"while":[129],"still":[130],"being":[131],"able":[132],"most":[135],"noise.":[138],"This":[139],"paper":[140],"proposes":[141],"mixed":[143],"method":[146],"harnesses":[148],"two":[149],"automatic":[151],"machine":[152,157],"learning":[153,158],"frameworks":[154],"train":[156],"models":[159,179],"using":[160],"results":[162,190],"several":[164],"algorithms":[166],"other":[168,193],"statistics.":[170],"Cross-validation":[171],"was":[172],"performed":[173],"ensure":[175],"selected":[178],"are":[180],"robust":[181],"perform":[183],"well":[184],"new":[186],"data.":[187],"We":[188],"obtained":[189],"comparable":[191],"with":[192],"state-of-the-art":[194],"methods":[195],"datasets.":[201]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-06-02T00:00:00"}
