{"id":"https://openalex.org/W211715088","doi":"https://doi.org/10.3217/jucs-017-01-0016","title":"Text Line Detection and Segmentation: Uneven Skew Angles and Hill-and-Dale Writing","display_name":"Text Line Detection and Segmentation: Uneven Skew Angles and Hill-and-Dale Writing","publication_year":2020,"publication_date":"2020-04-07","ids":{"openalex":"https://openalex.org/W211715088","doi":"https://doi.org/10.3217/jucs-017-01-0016","mag":"211715088"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.430.815","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.430.815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.jucs.org/jucs_17_1/text_line_detection_and/jucs_17_01_0016_0029_kavallieratou.pdf","raw_type":"text"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.3217/jucs-017-01-0016","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001210175","display_name":"Ergina Kavallieratou","orcid":"https://orcid.org/0000-0002-2815-3477"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ergina Kavallieratou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5064335707","display_name":"Fotis Daskas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fotis Daskas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.00083388,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"17","issue":null,"first_page":"16","last_page":"29"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.9797999858856201,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.8454267978668213},{"id":"https://openalex.org/keywords/skew","display_name":"Skew","score":0.8374694585800171},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.712139904499054},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.5936628580093384},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46980366110801697},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38162344694137573},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3302925229072571},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.24703431129455566},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09860336780548096},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06713271141052246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8454267978668213},{"id":"https://openalex.org/C43711488","wikidata":"https://www.wikidata.org/wiki/Q7534783","display_name":"Skew","level":2,"score":0.8374694585800171},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.712139904499054},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.5936628580093384},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46980366110801697},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38162344694137573},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3302925229072571},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.24703431129455566},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09860336780548096},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06713271141052246}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.430.815","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.430.815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.jucs.org/jucs_17_1/text_line_detection_and/jucs_17_01_0016_0029_kavallieratou.pdf","raw_type":"text"},{"id":"doi:10.3217/jucs-017-01-0016","is_oa":true,"landing_page_url":"https://doi.org/10.3217/jucs-017-01-0016","pdf_url":null,"source":{"id":"https://openalex.org/S4306400660","display_name":"TUGraz OPEN Library (Graz University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4092182","host_organization_name":"Graz University of Technology","host_organization_lineage":["https://openalex.org/I4092182"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"DataPaper"},{"id":"mag:211715088","is_oa":false,"landing_page_url":"https://dblp.uni-trier.de/db/journals/jucs/jucs17.html#KavallieratouD11","pdf_url":null,"source":{"id":"https://openalex.org/S58563349","display_name":"JUCS - Journal of Universal Computer Science","issn_l":"0948-695X","issn":["0948-695X","0948-6968"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310317875","host_organization_name":"Verlag der Technischen Universit\u00e4t Graz","host_organization_lineage":["https://openalex.org/P4310317875"],"host_organization_lineage_names":["Verlag der Technischen Universit\u00e4t Graz"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"JUCS - Journal of Universal Computer Science","raw_type":null}],"best_oa_location":{"id":"doi:10.3217/jucs-017-01-0016","is_oa":true,"landing_page_url":"https://doi.org/10.3217/jucs-017-01-0016","pdf_url":null,"source":{"id":"https://openalex.org/S4306400660","display_name":"TUGraz OPEN Library (Graz University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4092182","host_organization_name":"Graz University of Technology","host_organization_lineage":["https://openalex.org/I4092182"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"DataPaper"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2374501150","https://openalex.org/W2913812771","https://openalex.org/W2360905602","https://openalex.org/W2016645453","https://openalex.org/W2353244164","https://openalex.org/W3006011403","https://openalex.org/W2378349087","https://openalex.org/W2354863620","https://openalex.org/W2781599708","https://openalex.org/W2370422351"],"abstract_inverted_index":{"Abstract:":[0],"In":[1],"this":[2],"paper":[3],"a":[4],"line":[5],"detection":[6],"and":[7,58],"segmentation":[8,37],"technique":[9,14],"is":[10,15,61,73],"presented.":[11],"The":[12,23,53],"proposed":[13],"an":[16,20],"improved":[17],"version":[18,60],"of":[19,32,49],"older":[21,57],"one.":[22],"experiments":[24],"have":[25],"been":[26],"performed":[27],"on":[28],"the":[29,33,47,50,56,67],"training":[30],"dataset":[31],"ICDAR":[34],"2009":[35],"handwriting":[36],"contest":[38],"in":[39],"order":[40],"to":[41,44],"be":[42],"able":[43],"compare,":[45],"objectively,":[46],"performance":[48],"two":[51],"techniques.":[52],"improvement":[54],"between":[55],"newer":[59],"more":[62],"than":[63,75],"24":[64],"%":[65],"while":[66],"average":[68],"extra":[69],"CPU":[70],"time":[71],"cost":[72],"less":[74],"200":[76],"ms":[77],"per":[78],"page.":[79]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":5}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}