{"id":"https://openalex.org/W2510147818","doi":"https://doi.org/10.1109/icip.2016.7532961","title":"Signature line detection in scanned documents","display_name":"Signature line detection in scanned documents","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2510147818","doi":"https://doi.org/10.1109/icip.2016.7532961","mag":"2510147818"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7532961","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532961","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","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/A5007846616","display_name":"Osborn de Lima","orcid":null},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Osborn de Lima","raw_affiliation_strings":["Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044987052","display_name":"Shruty Janakiraman","orcid":null},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shruty Janakiraman","raw_affiliation_strings":["Department of Electrical and Microelectronic Engineering, Rochester Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Microelectronic Engineering, Rochester Institute of Technology","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110980789","display_name":"Eli Saber","orcid":"https://orcid.org/0009-0002-8593-4015"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eli Saber","raw_affiliation_strings":["Department of Electrical and Microelectronic Engineering, Rochester Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Microelectronic Engineering, Rochester Institute of Technology","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111373589","display_name":"David Day","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David C. Day","raw_affiliation_strings":["HP Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HP Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034794728","display_name":"P\u00e9ter Bauer","orcid":"https://orcid.org/0000-0002-1925-2270"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peter Bauer","raw_affiliation_strings":["HP Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HP Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046415827","display_name":"Mark Shaw","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mark Shaw","raw_affiliation_strings":["HP Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HP Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001181127","display_name":"Roger Twede","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roger Twede","raw_affiliation_strings":["HP Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HP Inc","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010594548","display_name":"Perry Lea","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Perry Lea","raw_affiliation_strings":["HP Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"HP Inc","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.07347617,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"31","issue":null,"first_page":"3254","last_page":"3258"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9994999766349792,"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":0.9990000128746033,"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/hough-transform","display_name":"Hough transform","score":0.8173074722290039},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6915799379348755},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.6775604486465454},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6618691086769104},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.65129554271698},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6408507823944092},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6289844512939453},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.5720446705818176},{"id":"https://openalex.org/keywords/line-segment","display_name":"Line segment","score":0.5154405832290649},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.5133899450302124},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.480579137802124},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45080772042274475},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2332891821861267},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21373018622398376}],"concepts":[{"id":"https://openalex.org/C200518788","wikidata":"https://www.wikidata.org/wiki/Q195076","display_name":"Hough transform","level":3,"score":0.8173074722290039},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6915799379348755},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.6775604486465454},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6618691086769104},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.65129554271698},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6408507823944092},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6289844512939453},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.5720446705818176},{"id":"https://openalex.org/C182124507","wikidata":"https://www.wikidata.org/wiki/Q166154","display_name":"Line segment","level":2,"score":0.5154405832290649},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.5133899450302124},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.480579137802124},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45080772042274475},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2332891821861267},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21373018622398376},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2016.7532961","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532961","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W95140590","https://openalex.org/W2054461204","https://openalex.org/W2128119911","https://openalex.org/W2128818553","https://openalex.org/W2132064754","https://openalex.org/W2151071493","https://openalex.org/W2161969291","https://openalex.org/W4251704781"],"related_works":["https://openalex.org/W2133640447","https://openalex.org/W2125790330","https://openalex.org/W2100522530","https://openalex.org/W1970655187","https://openalex.org/W581142974","https://openalex.org/W2349439813","https://openalex.org/W1920486319","https://openalex.org/W2093427527","https://openalex.org/W3180429661","https://openalex.org/W2376883242"],"abstract_inverted_index":{"In":[0],"this":[1,40,124],"paper,":[2],"we":[3],"present":[4],"an":[5],"algorithm":[6,26,141],"to":[7,49,76,82,94],"determine":[8],"the":[9,25,53,67,83,87,90],"signature":[10,100],"line":[11,34,50,68,85,97,101],"in":[12,39,52,66,133,145],"scanned":[13],"documents":[14],"through":[15],"a":[16,60,99,110,115],"fast":[17],"and":[18,36,114,137,149],"computationally":[19],"efficient":[20],"technique.":[21],"To":[22],"that":[23],"effect,":[24],"consists":[27,42,127],"of":[28,43,109,128,130,147],"three":[29],"modules,":[30],"namely":[31],"pre-processing,":[32],"candidate":[33],"detection":[35,51,69],"classification.":[37],"Preprocessing":[38],"case":[41],"hard":[44],"thresholding,":[45],"which":[46],"is":[47,64,74,105],"essential":[48],"next":[54],"module.":[55,70],"The":[56,139],"Hough":[57,79],"transform":[58],"for":[59,119,123],"single":[61],"angle":[62],"(horizontal)":[63],"utilized":[65,75],"Connected":[71],"component":[72],"analysis":[73],"merge":[77],"detected":[78],"lines":[80],"belonging":[81],"same":[84],"on":[86],"document.":[88],"Finally,":[89],"classification":[91],"module":[92],"attempts":[93],"classify":[95],"each":[96],"as":[98],"or":[102],"not.":[103],"This":[104],"accomplished":[106],"using":[107],"Histogram":[108],"Gradient":[111],"(HoG)":[112],"features":[113],"Euclidean":[116],"distance":[117],"measure":[118],"comparison.":[120],"Prior":[121],"data":[122],"similarity":[125],"comparison":[126],"images":[129],"target":[131],"text":[132],"different":[134],"font":[135],"sizes":[136],"styles.":[138],"proposed":[140],"showed":[142],"favorable":[143],"results":[144],"terms":[146],"precision":[148],"accuracy.":[150]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
