{"id":"https://openalex.org/W2069456987","doi":"https://doi.org/10.1145/1860559.1860604","title":"Degraded dot matrix character recognition using CSM-based feature extraction","display_name":"Degraded dot matrix character recognition using CSM-based feature extraction","publication_year":2010,"publication_date":"2010-09-21","ids":{"openalex":"https://openalex.org/W2069456987","doi":"https://doi.org/10.1145/1860559.1860604","mag":"2069456987"},"language":"en","primary_location":{"id":"doi:10.1145/1860559.1860604","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1860559.1860604","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM symposium on Document engineering","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/A5036899618","display_name":"Abdelkader Namane","orcid":"https://orcid.org/0000-0001-7180-7619"},"institutions":[{"id":"https://openalex.org/I83332908","display_name":"University of Blida","ror":"https://ror.org/03g41pw14","country_code":"DZ","type":"education","lineage":["https://openalex.org/I83332908"]}],"countries":["DZ"],"is_corresponding":true,"raw_author_name":"Abderrahmane Namane","raw_affiliation_strings":["University Saad Dahlab of Blida, Blida, Algeria"],"affiliations":[{"raw_affiliation_string":"University Saad Dahlab of Blida, Blida, Algeria","institution_ids":["https://openalex.org/I83332908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084594076","display_name":"E. H. Soubari","orcid":null},"institutions":[{"id":"https://openalex.org/I68947357","display_name":"Universit\u00e9 de Strasbourg","ror":"https://ror.org/00pg6eq24","country_code":"FR","type":"education","lineage":["https://openalex.org/I68947357"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"El Houssine Soubari","raw_affiliation_strings":["University of Strasbourg, Strasbourg, France"],"affiliations":[{"raw_affiliation_string":"University of Strasbourg, Strasbourg, France","institution_ids":["https://openalex.org/I68947357"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051817794","display_name":"Patrick Meyrueis","orcid":null},"institutions":[{"id":"https://openalex.org/I68947357","display_name":"Universit\u00e9 de Strasbourg","ror":"https://ror.org/00pg6eq24","country_code":"FR","type":"education","lineage":["https://openalex.org/I68947357"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Patrick Meyrueis","raw_affiliation_strings":["University of Strasbourg, Strasbourg, France"],"affiliations":[{"raw_affiliation_string":"University of Strasbourg, Strasbourg, France","institution_ids":["https://openalex.org/I68947357"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036899618"],"corresponding_institution_ids":["https://openalex.org/I83332908"],"apc_list":null,"apc_paid":null,"fwci":0.3187,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.60419578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"207","last_page":"210"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9952999949455261,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9868000149726868,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7500184774398804},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.7261150479316711},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7172022461891174},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6941097378730774},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5936936736106873},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.5793488025665283},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.513340413570404},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4693376123905182},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44150134921073914},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4144141674041748},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24896582961082458},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18907883763313293},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14134585857391357}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7500184774398804},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.7261150479316711},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7172022461891174},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6941097378730774},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5936936736106873},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.5793488025665283},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.513340413570404},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4693376123905182},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44150134921073914},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4144141674041748},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24896582961082458},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18907883763313293},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14134585857391357},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1860559.1860604","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1860559.1860604","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM symposium on Document engineering","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":7,"referenced_works":["https://openalex.org/W2016866522","https://openalex.org/W2028504087","https://openalex.org/W2066002465","https://openalex.org/W2094306970","https://openalex.org/W2107768760","https://openalex.org/W2111822866","https://openalex.org/W2144839447"],"related_works":["https://openalex.org/W3082848404","https://openalex.org/W1979583797","https://openalex.org/W2016864125","https://openalex.org/W2372254676","https://openalex.org/W2080135837","https://openalex.org/W2793679056","https://openalex.org/W2945706271","https://openalex.org/W4387435415","https://openalex.org/W2114169842","https://openalex.org/W2535808783"],"abstract_inverted_index":{"This":[0],"paper":[1,30],"presents":[2],"an":[3,21,109],"OCR":[4],"method":[5,87,95],"for":[6,161],"degraded":[7,72,182],"character":[8],"recognition":[9,86,179],"applied":[10],"to":[11,74,105,151,174],"a":[12,54,84,120,125,147],"reference":[13,37,56],"number":[14,38],"(RN)":[15],"of":[16,20,35,58,64,114,128,143,171],"15":[17],"printed":[18,55,183],"characters":[19,45,69,79],"invoice":[22],"document":[23],"produced":[24],"by":[25],"dot-matrix":[26],"printer.":[27],"First,":[28],"the":[29,33,36,44,59,67,78,90,116,144,153,169,172],"deals":[31],"with":[32,53],"problem":[34],"localization":[39],"and":[40,96,123,157,177],"extraction,":[41],"in":[42,77],"which":[43],"tops":[46,80],"or":[47,50,81,107],"bottoms":[48],"are":[49,70],"not":[51],"touched":[52,65],"line":[57],"electrical":[60,166],"bill.":[61],"In":[62,112],"case":[63,113],"RN,":[66],"extracted":[68],"severely":[71,181],"leading":[73],"missing":[75],"parts":[76],"bottoms.":[82],"Secondly,":[83],"combined":[85],"based":[88],"on":[89,165,180],"complementary":[91],"similarity":[92],"measure":[93],"(CSM)":[94],"MLP-based":[97],"classifier":[98],"is":[99,103,134],"used.":[100],"The":[101,132,141],"CSM":[102,117,145],"used":[104],"accept":[106],"reject":[108],"incoming":[110],"character.":[111],"acceptation,":[115],"acts":[118],"as":[119,146],"feature":[121,126,139,148],"extractor":[122,149],"produces":[124],"vector":[127],"ten":[129],"component":[130],"features.":[131],"MLP":[133,154],"then":[135],"trained":[136],"using":[137],"these":[138],"vectors.":[140],"use":[142],"tends":[150],"make":[152],"very":[155,158],"powerful":[156],"well":[159],"suited":[160],"rejection.":[162],"Experimental":[163],"results":[164],"bills":[167],"show":[168],"ability":[170],"model":[173],"yield":[175],"relevant":[176],"robust":[178],"characters.":[184]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}