{"id":"https://openalex.org/W2052881412","doi":"https://doi.org/10.1145/1815330.1815347","title":"Overlapped text segmentation using Markov random field and aggregation","display_name":"Overlapped text segmentation using Markov random field and aggregation","publication_year":2010,"publication_date":"2010-06-09","ids":{"openalex":"https://openalex.org/W2052881412","doi":"https://doi.org/10.1145/1815330.1815347","mag":"2052881412"},"language":"en","primary_location":{"id":"doi:10.1145/1815330.1815347","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1815330.1815347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th IAPR International Workshop on Document Analysis Systems","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/A5102329211","display_name":"Xujun Peng","orcid":"https://orcid.org/0000-0001-9373-7092"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xujun Peng","raw_affiliation_strings":["University at Buffalo, SUNY, Amherst, NY","University at Buffalo - SUNY, Amherst, NY#TAB#"],"affiliations":[{"raw_affiliation_string":"University at Buffalo, SUNY, Amherst, NY","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"University at Buffalo - SUNY, Amherst, NY#TAB#","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036052557","display_name":"Srirangaraj Setlur","orcid":"https://orcid.org/0000-0002-7118-9280"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Srirangaraj Setlur","raw_affiliation_strings":["University at Buffalo, SUNY, Amherst, NY","University at Buffalo - SUNY, Amherst, NY#TAB#"],"affiliations":[{"raw_affiliation_string":"University at Buffalo, SUNY, Amherst, NY","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"University at Buffalo - SUNY, Amherst, NY#TAB#","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020354604","display_name":"Venu Govindaraju","orcid":"https://orcid.org/0000-0002-5318-7409"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Venu Govindaraju","raw_affiliation_strings":["University at Buffalo, SUNY, Amherst, NY","University at Buffalo - SUNY, Amherst, NY#TAB#"],"affiliations":[{"raw_affiliation_string":"University at Buffalo, SUNY, Amherst, NY","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"University at Buffalo - SUNY, Amherst, NY#TAB#","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111810800","display_name":"Ramachandrula Sitaram","orcid":null},"institutions":[{"id":"https://openalex.org/I4210117576","display_name":"Hewlett-Packard (India)","ror":"https://ror.org/02ffkja82","country_code":"IN","type":"company","lineage":["https://openalex.org/I1324840837","https://openalex.org/I4210117576"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ramachandrula Sitaram","raw_affiliation_strings":["HP Labs India, Bangalore, India","[HP Laboratories, India, Bangalore, India]"],"affiliations":[{"raw_affiliation_string":"HP Labs India, Bangalore, India","institution_ids":["https://openalex.org/I4210117576"]},{"raw_affiliation_string":"[HP Laboratories, India, Bangalore, India]","institution_ids":["https://openalex.org/I4210117576"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102329211"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":2.231,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.88851584,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"129","last_page":"134"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9987999796867371,"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":0.9986000061035156,"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/markov-random-field","display_name":"Markov random field","score":0.7602930068969727},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7491142749786377},{"id":"https://openalex.org/keywords/handwriting","display_name":"Handwriting","score":0.7361068725585938},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6447409987449646},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6360392570495605},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.587888777256012},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5529530048370361},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.517113447189331},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5146608948707581},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.495821088552475},{"id":"https://openalex.org/keywords/handwriting-recognition","display_name":"Handwriting recognition","score":0.49524274468421936},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4898369014263153},{"id":"https://openalex.org/keywords/random-field","display_name":"Random field","score":0.44160810112953186},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4218355715274811},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19481396675109863},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.1689521074295044},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16013798117637634},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06640136241912842}],"concepts":[{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.7602930068969727},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7491142749786377},{"id":"https://openalex.org/C2779386606","wikidata":"https://www.wikidata.org/wiki/Q2393642","display_name":"Handwriting","level":2,"score":0.7361068725585938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6447409987449646},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6360392570495605},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.587888777256012},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5529530048370361},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.517113447189331},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5146608948707581},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.495821088552475},{"id":"https://openalex.org/C112640561","wikidata":"https://www.wikidata.org/wiki/Q2440634","display_name":"Handwriting recognition","level":3,"score":0.49524274468421936},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4898369014263153},{"id":"https://openalex.org/C130402806","wikidata":"https://www.wikidata.org/wiki/Q5361768","display_name":"Random field","level":2,"score":0.44160810112953186},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4218355715274811},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19481396675109863},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.1689521074295044},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16013798117637634},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06640136241912842},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1815330.1815347","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1815330.1815347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th IAPR International Workshop on Document Analysis Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7099999785423279,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W172100085","https://openalex.org/W2030837774","https://openalex.org/W2057175746","https://openalex.org/W2097074225","https://openalex.org/W2099212718","https://openalex.org/W2100617128","https://openalex.org/W2106666564","https://openalex.org/W2111522305","https://openalex.org/W2112525419","https://openalex.org/W2116862786","https://openalex.org/W2125378844","https://openalex.org/W2135164809","https://openalex.org/W2135249422","https://openalex.org/W2139565439","https://openalex.org/W2143363968","https://openalex.org/W2149760002","https://openalex.org/W2150753219","https://openalex.org/W2159080219","https://openalex.org/W4234544970","https://openalex.org/W6607119288","https://openalex.org/W6682346614"],"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":{"Separating":[0],"machine":[1,119],"printed":[2,120],"text":[3,8],"and":[4,18,87,90,115],"handwriting":[5,37,114],"from":[6,38,83],"overlapping":[7],"is":[9,81,95],"a":[10,32,68,84,99],"challenging":[11],"problem":[12],"in":[13],"the":[14,75,88,93,106],"document":[15],"analysis":[16],"field":[17],"no":[19],"reliable":[20],"algorithms":[21],"have":[22],"been":[23],"developed":[24],"thus":[25],"far.":[26],"In":[27],"this":[28],"paper,":[29],"we":[30,51],"propose":[31],"novel":[33],"approach":[34],"for":[35,113,118],"separating":[36],"binary":[39],"image":[40],"of":[41,45,92],"overlapped":[42,76],"text.":[43,77,121],"Instead":[44],"using":[46],"fixed":[47],"size":[48],"training":[49,63],"patches,":[50],"describe":[52],"an":[53],"aggregation":[54],"method":[55,108],"which":[56],"uses":[57],"shape":[58],"context":[59],"features":[60],"to":[61,73],"extract":[62],"samples":[64],"automatically.":[65],"We":[66],"use":[67],"Markov":[69],"Random":[70],"Field":[71],"(MRF)":[72],"model":[74],"The":[78],"neighbor":[79],"system":[80],"inherited":[82],"coarsening":[85],"procedure":[86],"prior":[89],"likelihood":[91],"MRF":[94],"learned":[96],"based":[97],"on":[98],"distance":[100],"metric.":[101],"Experimental":[102],"results":[103],"show":[104],"that":[105],"proposed":[107],"can":[109],"achieve":[110],"87.97%":[111],"recall":[112,117],"91.44%":[116]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}