{"id":"https://openalex.org/W2998784017","doi":"https://doi.org/10.1109/jas.2019.1911843","title":"A local contrast fusion based 3D Otsu algorithm for multilevel image segmentation","display_name":"A local contrast fusion based 3D Otsu algorithm for multilevel image segmentation","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2998784017","doi":"https://doi.org/10.1109/jas.2019.1911843","mag":"2998784017"},"language":"en","primary_location":{"id":"doi:10.1109/jas.2019.1911843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jas.2019.1911843","pdf_url":null,"source":{"id":"https://openalex.org/S2484288132","display_name":"IEEE/CAA Journal of Automatica Sinica","issn_l":"2329-9266","issn":["2329-9266","2329-9274"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/CAA Journal of Automatica Sinica","raw_type":"journal-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/A5066467382","display_name":"Ashish Kumar Bhandari","orcid":"https://orcid.org/0000-0001-9842-8125"},"institutions":[{"id":"https://openalex.org/I11793825","display_name":"National Institute of Technology Patna","ror":"https://ror.org/056wyhh33","country_code":"IN","type":"education","lineage":["https://openalex.org/I11793825","https://openalex.org/I4210152752"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ashish Kumar Bhandari","raw_affiliation_strings":["Department of Electronics and Communication Engineering, National Institute of Technology Patna, Bihar 800005, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, National Institute of Technology Patna, Bihar 800005, India","institution_ids":["https://openalex.org/I11793825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086784180","display_name":"Arunangshu Ghosh","orcid":"https://orcid.org/0000-0001-9712-172X"},"institutions":[{"id":"https://openalex.org/I11793825","display_name":"National Institute of Technology Patna","ror":"https://ror.org/056wyhh33","country_code":"IN","type":"education","lineage":["https://openalex.org/I11793825","https://openalex.org/I4210152752"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arunangshu Ghosh","raw_affiliation_strings":["Department of Electronics and Communication Engineering, National Institute of Technology Patna, Bihar 800005, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, National Institute of Technology Patna, Bihar 800005, India","institution_ids":["https://openalex.org/I11793825"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034009215","display_name":"Immadisetty Vinod Kumar","orcid":"https://orcid.org/0000-0002-2331-9423"},"institutions":[{"id":"https://openalex.org/I11793825","display_name":"National Institute of Technology Patna","ror":"https://ror.org/056wyhh33","country_code":"IN","type":"education","lineage":["https://openalex.org/I11793825","https://openalex.org/I4210152752"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Immadisetty Vinod Kumar","raw_affiliation_strings":["Department of Electronics and Communication Engineering, National Institute of Technology Patna, Bihar 800005, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, National Institute of Technology Patna, Bihar 800005, India","institution_ids":["https://openalex.org/I11793825"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I11793825"],"apc_list":null,"apc_paid":null,"fwci":6.6961,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.96886475,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"7","issue":"1","first_page":"200","last_page":"213"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9969000220298767,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/otsus-method","display_name":"Otsu's method","score":0.9380893111228943},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.8595420122146606},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.735649049282074},{"id":"https://openalex.org/keywords/balanced-histogram-thresholding","display_name":"Balanced histogram thresholding","score":0.702778697013855},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6415331363677979},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6285381317138672},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6161868572235107},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.536666989326477},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5137580633163452},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5078957676887512},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.483005166053772},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4657156467437744},{"id":"https://openalex.org/keywords/region-growing","display_name":"Region growing","score":0.4173853397369385},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4154682457447052},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4108327031135559},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.33192309737205505},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.3268320560455322}],"concepts":[{"id":"https://openalex.org/C21729346","wikidata":"https://www.wikidata.org/wiki/Q2444417","display_name":"Otsu's method","level":4,"score":0.9380893111228943},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.8595420122146606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.735649049282074},{"id":"https://openalex.org/C202577368","wikidata":"https://www.wikidata.org/wiki/Q2576067","display_name":"Balanced histogram thresholding","level":5,"score":0.702778697013855},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6415331363677979},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6285381317138672},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6161868572235107},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.536666989326477},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5137580633163452},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5078957676887512},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.483005166053772},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4657156467437744},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.4173853397369385},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4154682457447052},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4108327031135559},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.33192309737205505},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.3268320560455322},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C136943445","wikidata":"https://www.wikidata.org/wiki/Q1970240","display_name":"Histogram equalization","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jas.2019.1911843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jas.2019.1911843","pdf_url":null,"source":{"id":"https://openalex.org/S2484288132","display_name":"IEEE/CAA Journal of Automatica Sinica","issn_l":"2329-9266","issn":["2329-9266","2329-9274"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/CAA Journal of Automatica Sinica","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1493163589","https://openalex.org/W1996248842","https://openalex.org/W2001619934","https://openalex.org/W2024746652","https://openalex.org/W2027091505","https://openalex.org/W2037369677","https://openalex.org/W2119765017","https://openalex.org/W2120627761","https://openalex.org/W2133059825","https://openalex.org/W2135715608","https://openalex.org/W2136596830","https://openalex.org/W2171783278","https://openalex.org/W2352308485","https://openalex.org/W2508032853","https://openalex.org/W2543830482","https://openalex.org/W2552163569","https://openalex.org/W2613146779","https://openalex.org/W2754691136","https://openalex.org/W2894531915","https://openalex.org/W2895416280","https://openalex.org/W2911109763","https://openalex.org/W2920865086","https://openalex.org/W2943995207","https://openalex.org/W2945195937","https://openalex.org/W2950829012","https://openalex.org/W2964758591"],"related_works":["https://openalex.org/W2062132974","https://openalex.org/W3208096869","https://openalex.org/W2075538113","https://openalex.org/W2092478792","https://openalex.org/W2356757465","https://openalex.org/W2045808695","https://openalex.org/W2587771400","https://openalex.org/W3009452902","https://openalex.org/W2356620013","https://openalex.org/W4361990852"],"abstract_inverted_index":{"To":[0],"overcome":[1],"the":[2,12,28,33,42,66,70,76,103,124,142,156,179],"shortcomings":[3],"of":[4,44,75,85,114,129,144,148],"1D":[5,168],"and":[6,49,88,90,150,172,181],"2D":[7,170],"Otsu\u02bc":[8,21],"s":[9,22],"thresholding":[10,35,52,125],"techniques,":[11],"3D":[13,24,67,173],"Otsu":[14,25,68,171,174],"method":[15,53,158],"has":[16],"been":[17],"developed.":[18],"Among":[19],"all":[20],"methods,":[23,175],"technique":[26],"provides":[27],"best":[29],"threshold":[30,96],"values":[31,108],"for":[32],"multi-level":[34],"processes.":[36],"In":[37],"this":[38],"paper,":[39],"to":[40,119,166],"improve":[41,120,136],"quality":[43,81],"segmented":[45],"images,":[46],"a":[47,110],"simple":[48],"effective":[50],"multilevel":[51],"is":[54],"introduced.":[55],"The":[56,73,98,127],"proposed":[57,157],"approach":[58,100],"focuses":[59],"on":[60,132],"preserving":[61],"edge":[62],"detail":[63],"by":[64,140],"computing":[65],"along":[69],"fusion":[71,99,128],"phenomena.":[72],"advantages":[74],"presented":[77],"scheme":[78],"include":[79],"higher":[80],"outcomes,":[82],"better":[83],"preservation":[84],"tiny":[86],"details":[87,149],"boundaries":[89],"reduced":[91],"execution":[92],"time":[93],"with":[94],"rising":[95],"levels.":[97],"depends":[101],"upon":[102],"differences":[104],"between":[105],"pixel":[106],"intensity":[107],"within":[109],"small":[111],"local":[112,133,145],"space":[113],"an":[115],"image;":[116],"it":[117],"aims":[118],"localized":[121],"information":[122],"after":[123],"process.":[126],"images":[130],"based":[131],"contrast":[134],"can":[135],"image":[137],"segmentation":[138,162],"performance":[139],"minimizing":[141],"loss":[143,147],"contrast,":[146],"gray-level":[151],"distributions.":[152],"Results":[153],"show":[154],"that":[155],"yields":[159],"more":[160],"promising":[161],"results":[163],"when":[164],"compared":[165],"conventional":[167],"Otsu,":[169],"as":[176],"evident":[177],"from":[178],"objective":[180],"subjective":[182],"evaluations.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":4}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}