{"id":"https://openalex.org/W2905549297","doi":"https://doi.org/10.1145/3286606.3286831","title":"Lines segmentation and word extraction of Arabic handwritten text","display_name":"Lines segmentation and word extraction of Arabic handwritten text","publication_year":2018,"publication_date":"2018-10-10","ids":{"openalex":"https://openalex.org/W2905549297","doi":"https://doi.org/10.1145/3286606.3286831","mag":"2905549297"},"language":"en","primary_location":{"id":"doi:10.1145/3286606.3286831","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3286606.3286831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Smart City Applications","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/A5032157402","display_name":"Asmae Lamsaf","orcid":"https://orcid.org/0000-0001-9410-5310"},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Asmae Lamsaf","raw_affiliation_strings":["LaRIT, Ibn Tofail University, Kenitra, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LaRIT, Ibn Tofail University, Kenitra, Morocco","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017201329","display_name":"Mounir Aitkerroum","orcid":null},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Mounir Aitkerroum","raw_affiliation_strings":["LaRIT, Ibn Tofail University, Kenitra, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LaRIT, Ibn Tofail University, Kenitra, Morocco","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067752066","display_name":"Siham Boulaknadel","orcid":"https://orcid.org/0000-0001-7538-7295"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siham Boulaknadel","raw_affiliation_strings":["IRCAM, Madinat Al Irfane, Rabat-Instituts Rabat, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IRCAM, Madinat Al Irfane, Rabat-Instituts Rabat, Morocco","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089704230","display_name":"Youssef Fakhri","orcid":"https://orcid.org/0000-0002-5647-303X"},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Youssef Fakhri","raw_affiliation_strings":["LaRIT, Ibn Tofail University, Kenitra, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LaRIT, Ibn Tofail University, Kenitra, Morocco","institution_ids":["https://openalex.org/I3121676899"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.318,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.64342633,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"6","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":1.0,"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":1.0,"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":0.9922000169754028,"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":0.9916999936103821,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7587049603462219},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6450707912445068},{"id":"https://openalex.org/keywords/connected-component","display_name":"Connected component","score":0.6432060599327087},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6263353228569031},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.6170266270637512},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5872095823287964},{"id":"https://openalex.org/keywords/handwriting","display_name":"Handwriting","score":0.5604795813560486},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5553544759750366},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5263843536376953},{"id":"https://openalex.org/keywords/handwriting-recognition","display_name":"Handwriting recognition","score":0.5163828134536743},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.4881904721260071},{"id":"https://openalex.org/keywords/arabic","display_name":"Arabic","score":0.4439210295677185},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44375577569007874},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43759748339653015},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33108556270599365},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19973766803741455},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.14326316118240356}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7587049603462219},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6450707912445068},{"id":"https://openalex.org/C193435613","wikidata":"https://www.wikidata.org/wiki/Q2997928","display_name":"Connected component","level":2,"score":0.6432060599327087},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6263353228569031},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.6170266270637512},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5872095823287964},{"id":"https://openalex.org/C2779386606","wikidata":"https://www.wikidata.org/wiki/Q2393642","display_name":"Handwriting","level":2,"score":0.5604795813560486},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5553544759750366},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5263843536376953},{"id":"https://openalex.org/C112640561","wikidata":"https://www.wikidata.org/wiki/Q2440634","display_name":"Handwriting recognition","level":3,"score":0.5163828134536743},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.4881904721260071},{"id":"https://openalex.org/C96455323","wikidata":"https://www.wikidata.org/wiki/Q13955","display_name":"Arabic","level":2,"score":0.4439210295677185},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44375577569007874},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43759748339653015},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33108556270599365},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19973766803741455},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.14326316118240356},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3286606.3286831","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3286606.3286831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Smart City Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W107907422","https://openalex.org/W1931650175","https://openalex.org/W1940869631","https://openalex.org/W1968983105","https://openalex.org/W1980175331","https://openalex.org/W2026927694","https://openalex.org/W2060746081","https://openalex.org/W2063997600","https://openalex.org/W2093100897","https://openalex.org/W2105373837","https://openalex.org/W2107249111","https://openalex.org/W2127895227","https://openalex.org/W2133059825","https://openalex.org/W2148645152","https://openalex.org/W2155896958","https://openalex.org/W2170325377","https://openalex.org/W2171927392","https://openalex.org/W2330004233","https://openalex.org/W2475102873","https://openalex.org/W2525112519","https://openalex.org/W2556927167","https://openalex.org/W2578215108","https://openalex.org/W2930015440"],"related_works":["https://openalex.org/W3003949997","https://openalex.org/W2110485610","https://openalex.org/W3199359807","https://openalex.org/W3047607512","https://openalex.org/W4390983538","https://openalex.org/W2744690920","https://openalex.org/W2787081548","https://openalex.org/W183832189","https://openalex.org/W2536878212","https://openalex.org/W1644732402"],"abstract_inverted_index":{"Words":[0],"are":[1,18,42,212],"often":[2],"a":[3,114,218],"succession":[4],"of":[5,34,78,84,90,96,165,199,223],"sub-words":[6],"(characters,":[7],"connected":[8,32,47],"components)":[9],"separated":[10],"by":[11,58],"spaces,":[12],"in":[13,53,63,130,156,179],"Arabic":[14,64,201],"handwritten":[15],"its":[16,137],"spaces":[17,28,43,97,102],"divided":[19],"into":[20,107,146,154],"two":[21,31,46,50],"types:":[22],"the":[23,27,35,39,59,82,94,105,120,125,131,143,169,171,176,183,187,196,200,209],"first":[24],"type":[25,41],"represents":[26],"that":[29,44,116],"separate":[30,45],"components":[33,48],"same":[36],"word":[37,220],"(within-word).":[38],"second":[40,60],"from":[49],"different":[51],"words(between-words).":[52],"our":[54,160],"work":[55],"we":[56,112,216],"designate":[57],"type.":[61],"Spaces":[62],"handwriting":[65,202],"do":[66],"not":[67,128],"respect":[68],"any":[69],"rule":[70],"because":[71],"each":[72,123,133,163],"person":[73],"has":[74],"his":[75],"own":[76],"style":[77],"writing,":[79],"which":[80],"increases":[81],"difficulty":[83],"segmentation":[85,189],"between":[86],"words.":[87,108],"The":[88],"extraction":[89,221],"words":[91],"based":[92],"on":[93,195],"classification":[95,138],"detected":[98],"and":[99,208],"extracts":[100],"between-words":[101],"to":[103,118,151,158,162,175,181],"segment":[104,152],"text":[106,144,177,205],"In":[109],"this":[110],"paper,":[111],"present":[113],"method":[115,161,185],"aims":[117],"compute":[119],"threshold":[121,126,139],"for":[122,186,204],"line,":[124],"is":[127,135,149,173,193],"fixed":[129],"document,":[132],"line":[134,164,188],"associated":[136],"spaces.":[140],"Before":[141],"segmenting":[142],"image":[145],"words,":[147],"it":[148,153],"necessary":[150],"lines":[155],"order":[157,180],"apply":[159,182],"text.":[166],"To":[167],"extract":[168],"lines,":[170],"preprocessing":[172],"applied":[174,194],"images":[178],"proposed":[184],"step.":[190],"Our":[191],"system":[192],"benchmarking":[197],"datasets":[198],"database":[203],"recognition":[206],"(AHDB)":[207],"experimental":[210],"results":[211],"very":[213],"promising":[214],"as":[215],"achieved":[217],"success":[219],"rate":[222],"87.9%.":[224]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
