{"id":"https://openalex.org/W2296275466","doi":"https://doi.org/10.1109/icip.2015.7351722","title":"Efficient 2\u00d72 block-based connected components labeling algorithms","display_name":"Efficient 2\u00d72 block-based connected components labeling algorithms","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2296275466","doi":"https://doi.org/10.1109/icip.2015.7351722","mag":"2296275466"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2015.7351722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351722","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 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/A5075064814","display_name":"Di\u00eago J. C. Santiago","orcid":null},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Diego J.C. Santiago","raw_affiliation_strings":["Center for Informatics, Federal University of Pemambuco Recife, PE, Brazil"],"affiliations":[{"raw_affiliation_string":"Center for Informatics, Federal University of Pemambuco Recife, PE, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022457755","display_name":"Tsang Ing Ren","orcid":"https://orcid.org/0000-0002-3677-0264"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Tsang Ing Ren","raw_affiliation_strings":["Center for Informatics, Federal University of Pernambuco, Recife, PE, BR"],"affiliations":[{"raw_affiliation_string":"Center for Informatics, Federal University of Pernambuco, Recife, PE, BR","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084140678","display_name":"George D. C. Cavalcanti","orcid":"https://orcid.org/0000-0001-7714-2283"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"George D.C. Cavalcanti","raw_affiliation_strings":["Center for Informatics, Federal University of Pemambuco Recife, PE, Brazil"],"affiliations":[{"raw_affiliation_string":"Center for Informatics, Federal University of Pemambuco Recife, PE, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020571781","display_name":"Tsang Ing Jyh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tsang Ing Jyh","raw_affiliation_strings":["Alcatel-Lucent, Belgium"],"affiliations":[{"raw_affiliation_string":"Alcatel-Lucent, Belgium","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5075064814"],"corresponding_institution_ids":["https://openalex.org/I25112270"],"apc_list":null,"apc_paid":null,"fwci":0.1872,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.61950312,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"4818","last_page":"4822"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12923","display_name":"Digital Image Processing 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/T12923","display_name":"Digital Image Processing 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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9965999722480774,"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":0.9860000014305115,"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/pixel","display_name":"Pixel","score":0.863853931427002},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.8405577540397644},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7651599049568176},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5924266576766968},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5478512644767761},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4715288579463959},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.45211634039878845},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3968508839607239},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.384630411863327},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17693933844566345}],"concepts":[{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.863853931427002},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.8405577540397644},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7651599049568176},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5924266576766968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5478512644767761},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4715288579463959},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.45211634039878845},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3968508839607239},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.384630411863327},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17693933844566345},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2015.7351722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351722","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W170294175","https://openalex.org/W1482166000","https://openalex.org/W1499584250","https://openalex.org/W1971615118","https://openalex.org/W1973425785","https://openalex.org/W1975157055","https://openalex.org/W1990491759","https://openalex.org/W1991239220","https://openalex.org/W2010426345","https://openalex.org/W2012404882","https://openalex.org/W2012743170","https://openalex.org/W2040582952","https://openalex.org/W2051685651","https://openalex.org/W2053145534","https://openalex.org/W2068113013","https://openalex.org/W2071355008","https://openalex.org/W2112264963","https://openalex.org/W2120646872","https://openalex.org/W2129042353","https://openalex.org/W2130452018","https://openalex.org/W2148556285","https://openalex.org/W2151948813","https://openalex.org/W2158240273","https://openalex.org/W4256068510","https://openalex.org/W7011739198"],"related_works":["https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W4390494008","https://openalex.org/W2922442631","https://openalex.org/W2053596378","https://openalex.org/W2168523118","https://openalex.org/W2073639911","https://openalex.org/W2043988397"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2,145],"three":[3],"new":[4,39],"efficient":[5],"2\u00d72":[6,65],"block-based":[7,66,142,161],"algorithms":[8,67],"for":[9],"connected":[10],"components":[11],"labeling:":[12],"a":[13,21,30,72,75],"two-scan":[14,22,162],"which":[15,23,32,80,154,164],"assigns":[16,24,33,165],"provisional":[17,25,34,166],"labels":[18,26,35,167],"to":[19,27,36,47,100,113,127,136,168,171],"blocks,":[20],"pixels":[28,86,104,169],"and":[29,124],"one-and-a-half-scan":[31,143],"blocks.":[37],"A":[38],"stripe":[40],"image":[41],"representation":[42],"is":[43,109,155],"designed":[44],"in":[45,77,87,105,149,175,180],"order":[46],"perform":[48],"the":[49,54,63,78,88,93,102,106,129,132,137,146,150,173,176],"second":[50],"pass":[51],"only":[52],"through":[53],"blocks":[55],"containing":[56],"some":[57],"foreground":[58],"pixel.":[59],"We":[60,119],"also":[61],"improved":[62],"existing":[64,138],"by":[68],"utilizing":[69],"information":[70],"of":[71,83,96,117,131,157],"pixel":[73],"during":[74],"transition":[76],"mask,":[79],"allows":[81],"checking":[82,97],"four":[84],"neighbor":[85,103],"mask":[89],"at":[90],"most.":[91],"Thus,":[92],"average":[94],"number":[95],"operations":[98],"needed":[99],"inspect":[101],"first":[107],"scan":[108],"reduced":[110],"from":[111],"1.459":[112],"1.156,":[114],"an":[115],"improvement":[116],"21%.":[118],"conducted":[120],"experiments":[121],"using":[122],"synthetic":[123,177],"real":[125,151],"images":[126,152],"evaluate":[128],"performance":[130,148],"proposed":[133,141],"methods":[134],"compared":[135],"methods.":[139],"The":[140],"algorithm":[144,163],"best":[147],"dataset,":[153,178],"composed":[156],"1290":[158],"documents.":[159],"Our":[160],"showed":[170],"be":[172],"fastest":[174],"especially":[179],"high":[181],"density":[182],"images.":[183]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
