{"id":"https://openalex.org/W2023808019","doi":"https://doi.org/10.1142/s0219467815400069","title":"Background Ruled-Lines Detection and Removal in Full-Colored Handwritten Image Documents","display_name":"Background Ruled-Lines Detection and Removal in Full-Colored Handwritten Image Documents","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W2023808019","doi":"https://doi.org/10.1142/s0219467815400069","mag":"2023808019"},"language":"en","primary_location":{"id":"doi:10.1142/s0219467815400069","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467815400069","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"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 Image and Graphics","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/A5060264105","display_name":"Mohammed A. A. Refaey","orcid":null},"institutions":[{"id":"https://openalex.org/I145487455","display_name":"Cairo University","ror":"https://ror.org/03q21mh05","country_code":"EG","type":"education","lineage":["https://openalex.org/I145487455"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Mohammed A. A. Refaey","raw_affiliation_strings":["Information Technology Department, Faculty of Computers and Information, Cairo University, 5 Dr. Ahmed Zewail Street, Postal Code:12613, Orman, Giza, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Technology Department, Faculty of Computers and Information, Cairo University, 5 Dr. Ahmed Zewail Street, Postal Code:12613, Orman, Giza, Egypt","institution_ids":["https://openalex.org/I145487455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5060264105"],"corresponding_institution_ids":["https://openalex.org/I145487455"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0864989,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":"02","first_page":"1540006","last_page":"1540006"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9994999766349792,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9994000196456909,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9993000030517578,"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/computer-science","display_name":"Computer science","score":0.75315260887146},{"id":"https://openalex.org/keywords/optical-character-recognition","display_name":"Optical character recognition","score":0.7426838874816895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7251176238059998},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6213957071304321},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5727962851524353},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5222426652908325},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5042344331741333},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4982891082763672},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4687376618385315},{"id":"https://openalex.org/keywords/hough-transform","display_name":"Hough transform","score":0.45440998673439026},{"id":"https://openalex.org/keywords/binary-image","display_name":"Binary image","score":0.4505898058414459},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.4453917145729065},{"id":"https://openalex.org/keywords/hue","display_name":"Hue","score":0.4415213167667389},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.42767542600631714},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.30320268869400024},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15172475576400757}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.75315260887146},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.7426838874816895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7251176238059998},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6213957071304321},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5727962851524353},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5222426652908325},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5042344331741333},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4982891082763672},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4687376618385315},{"id":"https://openalex.org/C200518788","wikidata":"https://www.wikidata.org/wiki/Q195076","display_name":"Hough transform","level":3,"score":0.45440998673439026},{"id":"https://openalex.org/C193828747","wikidata":"https://www.wikidata.org/wiki/Q864118","display_name":"Binary image","level":4,"score":0.4505898058414459},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.4453917145729065},{"id":"https://openalex.org/C126537357","wikidata":"https://www.wikidata.org/wiki/Q372948","display_name":"Hue","level":2,"score":0.4415213167667389},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42767542600631714},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.30320268869400024},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15172475576400757},{"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:10.1142/s0219467815400069","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467815400069","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"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 Image and Graphics","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":9,"referenced_works":["https://openalex.org/W1966278896","https://openalex.org/W2035977559","https://openalex.org/W2036004749","https://openalex.org/W2068530900","https://openalex.org/W2075967370","https://openalex.org/W2139381235","https://openalex.org/W2145684309","https://openalex.org/W2152909144","https://openalex.org/W2544312983"],"related_works":["https://openalex.org/W4320518079","https://openalex.org/W2030098947","https://openalex.org/W2363834444","https://openalex.org/W2003466055","https://openalex.org/W2070077862","https://openalex.org/W2164944168","https://openalex.org/W4386771591","https://openalex.org/W262984167","https://openalex.org/W1978533094","https://openalex.org/W2009667652"],"abstract_inverted_index":{"Automation":[0],"becomes":[1],"the":[2,30,51,54,62,72,94,100,108,120,130,136,139,145,159,179,182],"standard":[3],"in":[4],"nearly":[5],"all":[6,155],"aspects":[7,13],"of":[8,11,50,56,85,99,104,144,153,181],"life.":[9],"Some":[10],"these":[12,86],"are":[14,67],"text":[15,32,46,60,137],"analysis,":[16],"translating":[17],"and":[18,69,83,96,114,124,166,188,192],"retrieval.":[19],"This":[20],"requires":[21,37,44],"machine":[22,34],"typed":[23],"format":[24],"as":[25,47],"a":[26],"preprocessing":[27],"step.":[28],"Converting":[29],"handwritten":[31,59],"into":[33],"printed":[35],"counterpart":[36],"Optical":[38],"Character":[39],"Recognition":[40],"(OCR)":[41],"system,":[42],"which":[43,66],"clean":[45,58],"input.":[48],"One":[49],"problems":[52],"facing":[53],"process":[55],"getting":[57,119],"is":[61,112,147,163,172],"ruled":[63,87,121,140],"background":[64],"lines":[65,122],"intersecting":[68],"mixed":[70],"with":[71,185],"text.":[73],"In":[74],"this":[75],"work,":[76],"we":[77],"present":[78],"fast":[79],"algorithms":[80,184],"for":[81,118,134,174,190],"detection":[82,90,191],"removal":[84,127,193],"lines.":[88,141],"The":[89,126,142,176],"stage":[91],"use":[92,115],"only":[93],"centralized":[95],"squared":[97],"part":[98],"image":[101,110,161,170],"document":[102,111,162],"instead":[103,152],"wasting":[105],"time":[106],"if":[107],"whole":[109],"used,":[113],"Hough":[116],"transform":[117],"location":[123],"direction.":[125],"algorithm":[128],"uses":[129],"color":[131,146,156],"histogram":[132],"segmentation":[133],"separating":[135],"from":[138],"Hue":[143],"used":[148],"to":[149,168],"represent":[150],"colors":[151],"using":[154],"components.":[157],"Then":[158],"segmented":[160],"morphologically":[164],"enhanced":[165],"converted":[167],"binary":[169],"that":[171],"suitable":[173],"OCR.":[175],"results":[177],"show":[178],"benefits":[180],"proposed":[183],"F1-measures":[186],"91.43%":[187],"88.52%":[189],"respectively.":[194]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
