{"id":"https://openalex.org/W2418596601","doi":"https://doi.org/10.1109/acpr.2015.7486591","title":"Text detection in born-digital images by mass estimation","display_name":"Text detection in born-digital images by mass estimation","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2418596601","doi":"https://doi.org/10.1109/acpr.2015.7486591","mag":"2418596601"},"language":"en","primary_location":{"id":"doi:10.1109/acpr.2015.7486591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2015.7486591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","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/A5081489097","display_name":"Jiamin Xu","orcid":"https://orcid.org/0000-0001-6749-1260"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiamin Xu","raw_affiliation_strings":["National Key Lab for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Key Lab for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025871978","display_name":"Palaiahnakote Shivakumara","orcid":"https://orcid.org/0000-0001-9026-4613"},"institutions":[{"id":"https://openalex.org/I33849332","display_name":"University of Malaya","ror":"https://ror.org/00rzspn62","country_code":"MY","type":"education","lineage":["https://openalex.org/I33849332"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Palaiahnakote Shivakumara","raw_affiliation_strings":["Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia","institution_ids":["https://openalex.org/I33849332"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061696740","display_name":"Tong L\u00fc","orcid":"https://orcid.org/0000-0002-7051-5347"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Lu","raw_affiliation_strings":["National Key Lab for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Key Lab for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111664929","display_name":"Chew Lim Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chew Lim Tan","raw_affiliation_strings":["School of Computing, National University of Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computing, National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045600512","display_name":"Michael Blumenstein","orcid":"https://orcid.org/0000-0002-9908-3744"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Michael Blumenstein","raw_affiliation_strings":["Griffith University, Gold Coast, Queensland, Australia"],"affiliations":[{"raw_affiliation_string":"Griffith University, Gold Coast, Queensland, Australia","institution_ids":["https://openalex.org/I11701301"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5081489097"],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":0.3744,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.71881721,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"690","last_page":"694"},"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9983000159263611,"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":0.9977999925613403,"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":0.7653216123580933},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6824474334716797},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.680366575717926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6354429721832275},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5755530595779419},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.5319222211837769},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.446979820728302},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4372670352458954},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4219357967376709},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36126285791397095},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3235740065574646}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7653216123580933},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6824474334716797},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.680366575717926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6354429721832275},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5755530595779419},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.5319222211837769},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.446979820728302},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4372670352458954},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4219357967376709},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36126285791397095},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3235740065574646}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/acpr.2015.7486591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2015.7486591","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/102966","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/102966","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/123854","is_oa":false,"landing_page_url":"http://hdl.handle.net/10072/123854","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1629468259","https://openalex.org/W1970556189","https://openalex.org/W1992747985","https://openalex.org/W1992986938","https://openalex.org/W2006408850","https://openalex.org/W2008806374","https://openalex.org/W2018451638","https://openalex.org/W2083868436","https://openalex.org/W2090914336","https://openalex.org/W2132122100","https://openalex.org/W2135231474","https://openalex.org/W2143973041","https://openalex.org/W2148214126","https://openalex.org/W2156038171","https://openalex.org/W2162075956","https://openalex.org/W2165707896","https://openalex.org/W2601974651","https://openalex.org/W2914923876","https://openalex.org/W4285719527","https://openalex.org/W6636699588","https://openalex.org/W6648170133","https://openalex.org/W6679460925","https://openalex.org/W6681891177"],"related_works":["https://openalex.org/W1557094818","https://openalex.org/W2183246718","https://openalex.org/W2099261052","https://openalex.org/W3209204065","https://openalex.org/W2090763504","https://openalex.org/W2105707930","https://openalex.org/W1755711892","https://openalex.org/W2160907113","https://openalex.org/W3135697610","https://openalex.org/W2070813941"],"abstract_inverted_index":{"There":[0],"is":[1],"a":[2,23,34,70,78,83,95,108],"need":[3],"for":[4,26,146],"effective":[5],"web-document":[6],"understanding":[7],"due":[8],"to":[9,40,48,63,82,86,99,120,133],"the":[10,88,104,143,147,158,167,171,175],"explosive":[11],"progress":[12],"of":[13,44,73,77,91],"internet":[14],"and":[15,60,157],"network":[16],"technologies.":[17],"In":[18],"this":[19],"paper,":[20],"we":[21],"propose":[22,39,69],"new":[24,71],"method":[25,56,145,173],"text":[27,50,66,80,101,118,123],"detection":[28],"in":[29,52,107,116],"born-digital":[30],"images":[31],"by":[32],"introducing":[33],"mass":[35,96],"estimation":[36,97],"concept.":[37],"We":[38,68,93,141],"explore":[41],"super-pixel":[42],"information":[43],"different":[45],"color":[46],"channels":[47],"identify":[49,64,100],"atoms":[51],"images.":[53],"The":[54,111,125],"proposed":[55,144,172],"uses":[57],"similarity":[58],"graphs":[59,114],"spectral":[61],"clustering":[62],"candidate":[65,79],"regions.":[67],"idea":[72],"mapping":[74],"Gabor":[75,127],"responses":[76,128],"region":[81],"spatial":[84,89,109],"circle":[85],"study":[87],"coherency":[90],"pixels.":[92],"introduce":[94],"concept":[98],"candidates":[102,119],"from":[103],"pixel":[105],"distribution":[106],"circle.":[110],"linear":[112],"linkage":[113],"help":[115],"grouping":[117],"obtain":[121],"full":[122],"lines.":[124],"same":[126],"are":[129],"used":[130],"as":[131,153],"features":[132],"eliminate":[134],"false":[135],"positives":[136],"with":[137],"an":[138],"SVM":[139],"classifier.":[140],"evaluate":[142],"testing":[148],"on":[149,165],"standard":[150],"datasets,":[151],"such":[152],"ICDAR":[154],"2013":[155],"(challenge-1)":[156],"Situ":[159],"et":[160],"al.":[161],"dataset.":[162],"Experimental":[163],"results":[164],"both":[166],"datasets":[168],"show":[169],"that":[170],"outperforms":[174],"existing":[176],"methods.":[177]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
