{"id":"https://openalex.org/W4415195054","doi":"https://doi.org/10.48550/arxiv.2508.06351","title":"An Implemention of Two-Phase Image Segmentation using the Split Bregman Method","display_name":"An Implemention of Two-Phase Image Segmentation using the Split Bregman Method","publication_year":2025,"publication_date":"2025-08-08","ids":{"openalex":"https://openalex.org/W4415195054","doi":"https://doi.org/10.48550/arxiv.2508.06351"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2508.06351","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.06351","pdf_url":"https://arxiv.org/pdf/2508.06351","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2508.06351","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058783345","display_name":"Olakunle S. Abawonse","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abawonse, Olakunle S.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5066059400","display_name":"G\u00fcnay Do\u011fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Do\u011fan, G\u00fcnay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.5085999965667725,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.5085999965667725,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T14319","display_name":"Currency Recognition and Detection","score":0.4447000026702881,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.4194999933242798,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/image-segmentation","display_name":"Image segmentation","score":0.7077999711036682},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6607999801635742},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5608999729156494},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5508000254631042},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.515999972820282},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4810999929904938},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.47920000553131104},{"id":"https://openalex.org/keywords/range-segmentation","display_name":"Range segmentation","score":0.4553999900817871},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4426000118255615}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.7077999711036682},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6644999980926514},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6607999801635742},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5608999729156494},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5572999715805054},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5508000254631042},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5365999937057495},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.515999972820282},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4810999929904938},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.47920000553131104},{"id":"https://openalex.org/C67561299","wikidata":"https://www.wikidata.org/wiki/Q7292710","display_name":"Range segmentation","level":5,"score":0.4553999900817871},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4426000118255615},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.415800005197525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3750999867916107},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3732999861240387},{"id":"https://openalex.org/C96133863","wikidata":"https://www.wikidata.org/wiki/Q6913458","display_name":"Morphological gradient","level":5,"score":0.36890000104904175},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3440999984741211},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.3203999996185303},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3102000057697296},{"id":"https://openalex.org/C42314347","wikidata":"https://www.wikidata.org/wiki/Q6865488","display_name":"Minimum spanning tree-based segmentation","level":5,"score":0.30820000171661377},{"id":"https://openalex.org/C191640071","wikidata":"https://www.wikidata.org/wiki/Q5377056","display_name":"Energy functional","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.28859999775886536},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.27880001068115234},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.26409998536109924},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.2540000081062317}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2508.06351","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.06351","pdf_url":"https://arxiv.org/pdf/2508.06351","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2508.06351","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2508.06351","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2508.06351","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.06351","pdf_url":"https://arxiv.org/pdf/2508.06351","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320308269","display_name":"Alexander von Humboldt-Stiftung","ror":"https://ror.org/012kf4317"},{"id":"https://openalex.org/F4320320875","display_name":"Deutscher Akademischer Austauschdienst","ror":"https://ror.org/039djdh30"},{"id":"https://openalex.org/F4320332178","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416"},{"id":"https://openalex.org/F4320337380","display_name":"Division of Mathematical Sciences","ror":"https://ror.org/051fftw81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1,167],"paper,":[2],"we":[3],"describe":[4],"an":[5,87,157],"implementation":[6,165],"of":[7,25,38,46,62,117,137,166,180],"the":[8,23,39,54,59,63,76,82,91,115,122,135,151],"two-phase":[9,159],"image":[10,29,40,65,118],"segmentation":[11,55],"algorithm":[12,21,181],"proposed":[13,105],"by":[14,69,106],"Goldstein,":[15,131],"Bresson,":[16,132],"Osher":[17,133],"in":[18,89,110,121,139],"\\cite{gold:bre}.":[19],"This":[20,112],"partitions":[22],"domain":[24],"a":[26,94,125,163,178],"given":[27],"2d":[28],"into":[30],"foreground":[31],"and":[32,35,74,108,124,170],"background":[33],"regions,":[34],"each":[36],"pixel":[37,60],"is":[41,57,84,93,114],"assigned":[42],"membership":[43,96],"to":[44,98,101,155],"one":[45],"these":[47],"two":[48,70],"regions.":[49],"The":[50],"underlying":[51],"assumption":[52],"for":[53,128],"model":[56,83],"that":[58,75,142],"values":[61],"input":[64],"can":[66,146],"be":[67,147],"summarized":[68],"distinct":[71],"average":[72],"values,":[73],"region":[77,95,129],"boundaries":[78],"are":[79],"smooth.":[80],"Accordingly,":[81],"defined":[85],"as":[86],"energy":[88,113,136,145],"which":[90],"variable":[92],"function":[97],"assign":[99],"pixels":[100],"either":[102],"region,":[103],"originally":[104],"Chan":[107],"Vese":[109],"\\cite{chan:vese}.":[111],"sum":[116],"data":[119],"terms":[120],"regions":[123],"length":[126],"penalty":[127],"boundaries.":[130],"modify":[134],"Chan-Vese":[138],"\\cite{gold:bre}":[140],"so":[141],"their":[143],"new":[144],"minimized":[148],"efficiently":[149],"using":[150],"split":[152],"Bregman":[153],"method":[154,168],"produce":[156],"equivalent":[158],"segmentation.":[160],"We":[161],"provide":[162],"detailed":[164],"\\cite{gold:bre},":[169],"document":[171],"its":[172],"performance":[173],"with":[174],"several":[175],"images":[176],"over":[177],"range":[179],"parameters.":[182]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-15T00:00:00"}
