{"id":"https://openalex.org/W2938033784","doi":"https://doi.org/10.3390/e21040398","title":"A Chaotic Electromagnetic Field Optimization Algorithm Based on Fuzzy Entropy for Multilevel Thresholding Color Image Segmentation","display_name":"A Chaotic Electromagnetic Field Optimization Algorithm Based on Fuzzy Entropy for Multilevel Thresholding Color Image Segmentation","publication_year":2019,"publication_date":"2019-04-15","ids":{"openalex":"https://openalex.org/W2938033784","doi":"https://doi.org/10.3390/e21040398","mag":"2938033784","pmid":"https://pubmed.ncbi.nlm.nih.gov/33267113"},"language":"en","primary_location":{"id":"doi:10.3390/e21040398","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e21040398","pdf_url":"https://www.mdpi.com/1099-4300/21/4/398/pdf?version=1555648187","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/21/4/398/pdf?version=1555648187","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008488180","display_name":"Suhang Song","orcid":"https://orcid.org/0000-0003-1934-632X"},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suhang Song","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China","institution_ids":["https://openalex.org/I47689461"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102744399","display_name":"Heming Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Heming Jia","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China"],"raw_orcid":"https://orcid.org/0000-0002-8256-9166","affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China","institution_ids":["https://openalex.org/I47689461"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101997874","display_name":"Jun Ma","orcid":"https://orcid.org/0000-0003-2258-0854"},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Ma","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China","institution_ids":["https://openalex.org/I47689461"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102744399"],"corresponding_institution_ids":["https://openalex.org/I47689461"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":2.8576,"has_fulltext":true,"cited_by_count":48,"citation_normalized_percentile":{"value":0.92799181,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"21","issue":"4","first_page":"398","last_page":"398"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9890999794006348,"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/T10057","display_name":"Face and Expression Recognition","score":0.9890999794006348,"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":0.9876999855041504,"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":0.9763000011444092,"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/thresholding","display_name":"Thresholding","score":0.8541264533996582},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.7314225435256958},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5968437194824219},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5895467400550842},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5308652520179749},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5294261574745178},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4215043783187866},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4155222177505493},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40557175874710083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3982393741607666},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.372453510761261},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3621065616607666},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.2505958378314972}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.8541264533996582},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.7314225435256958},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5968437194824219},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5895467400550842},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5308652520179749},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5294261574745178},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4215043783187866},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4155222177505493},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40557175874710083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3982393741607666},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.372453510761261},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3621065616607666},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2505958378314972},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e21040398","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e21040398","pdf_url":"https://www.mdpi.com/1099-4300/21/4/398/pdf?version=1555648187","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:33267113","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33267113","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:f77bce0cdca3496195cd25f1abd5f81f","is_oa":true,"landing_page_url":"https://doaj.org/article/f77bce0cdca3496195cd25f1abd5f81f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 21, Iss 4, p 398 (2019)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:7514892","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7514892","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e21040398","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e21040398","pdf_url":"https://www.mdpi.com/1099-4300/21/4/398/pdf?version=1555648187","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8600000143051147,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2938033784.pdf","grobid_xml":"https://content.openalex.org/works/W2938033784.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W331083581","https://openalex.org/W883434633","https://openalex.org/W978997059","https://openalex.org/W986100872","https://openalex.org/W1965118480","https://openalex.org/W1969351979","https://openalex.org/W1969774370","https://openalex.org/W1970442252","https://openalex.org/W1991927948","https://openalex.org/W1998843893","https://openalex.org/W2002131976","https://openalex.org/W2006010966","https://openalex.org/W2007508233","https://openalex.org/W2024746652","https://openalex.org/W2030161124","https://openalex.org/W2043245323","https://openalex.org/W2050787737","https://openalex.org/W2054097208","https://openalex.org/W2061438946","https://openalex.org/W2072955302","https://openalex.org/W2083970667","https://openalex.org/W2113490322","https://openalex.org/W2120627761","https://openalex.org/W2121766492","https://openalex.org/W2133059825","https://openalex.org/W2133665775","https://openalex.org/W2143001780","https://openalex.org/W2258223236","https://openalex.org/W2300017999","https://openalex.org/W2463752386","https://openalex.org/W2471964789","https://openalex.org/W2517312321","https://openalex.org/W2556422448","https://openalex.org/W2579979794","https://openalex.org/W2589233518","https://openalex.org/W2593487812","https://openalex.org/W2605810061","https://openalex.org/W2625302789","https://openalex.org/W2771026900","https://openalex.org/W2800075668","https://openalex.org/W2884996042","https://openalex.org/W2885736666","https://openalex.org/W2888125146","https://openalex.org/W2892295558","https://openalex.org/W2908929618","https://openalex.org/W2925456832","https://openalex.org/W3087867645","https://openalex.org/W6680096826","https://openalex.org/W6719096476","https://openalex.org/W6729752676","https://openalex.org/W6734772092","https://openalex.org/W6760907353"],"related_works":["https://openalex.org/W2138983844","https://openalex.org/W1968965685","https://openalex.org/W2012792772","https://openalex.org/W2356573839","https://openalex.org/W2111883783","https://openalex.org/W2009028679","https://openalex.org/W2357424838","https://openalex.org/W2327601824","https://openalex.org/W4237142086","https://openalex.org/W2981682705"],"abstract_inverted_index":{"Multilevel":[0],"thresholding":[1,232],"segmentation":[2,140,160,235],"of":[3,23,32,67,103,151,180,203,215,223],"color":[4,233],"images":[5,171],"is":[6,35,79,88,142],"an":[7,64],"important":[8],"technology":[9],"in":[10,18,29,49,82,178],"various":[11],"applications":[12],"which":[13,227],"has":[14],"received":[15],"more":[16],"attention":[17],"recent":[19],"years.":[20,60],"The":[21],"process":[22],"determining":[24],"the":[25,30,41,54,57,101,104,134,138,146,173,220,224],"optimal":[26],"threshold":[27,201],"values":[28],"case":[31],"traditional":[33],"methods":[34],"time-consuming.":[36],"In":[37,61],"order":[38],"to":[39,92,157,183],"mitigate":[40],"above":[42],"problem,":[43],"meta-heuristic":[44],"algorithms":[45,109],"have":[46],"been":[47],"employed":[48],"this":[50,62],"field":[51],"for":[52,209],"searching":[53],"optima":[55],"during":[56],"past":[58],"few":[59],"paper,":[63],"effective":[65],"technique":[66],"Electromagnetic":[68],"Field":[69],"Optimization":[70,121],"(EFO)":[71],"algorithm":[72,96],"based":[73],"on":[74,167],"a":[75,84,94],"fuzzy":[76,131],"entropy":[77,132,156],"criterion":[78],"proposed,":[80],"and":[81,123,154,162,172,194,207],"addition,":[83],"novel":[85],"chaotic":[86],"strategy":[87],"embedded":[89],"into":[90],"EFO":[91],"develop":[93],"new":[95],"named":[97],"CEFO.":[98],"To":[99],"evaluate":[100],"robustness":[102],"proposed":[105,139,225],"algorithm,":[106],"other":[107],"competitive":[108],"such":[110],"as":[111,133],"Artificial":[112],"Bee":[113],"Colony":[114],"(ABC),":[115],"Bat":[116],"Algorithm":[117,126],"(BA),":[118],"Wind":[119],"Driven":[120],"(WDO),":[122],"Bird":[124],"Swarm":[125],"(BSA)":[127],"are":[128,165,176],"compared":[129,144],"using":[130],"fitness":[135],"function.":[136],"Furthermore,":[137],"method":[141],"also":[143],"with":[145,230],"most":[147],"widely":[148],"used":[149],"approaches":[150],"Otsu's":[152],"variance":[153],"Kapur's":[155],"verify":[158],"its":[159],"accuracy":[161],"efficiency.":[163],"Experiments":[164],"conducted":[166],"ten":[168],"Berkeley":[169],"benchmark":[170],"simulation":[174],"results":[175],"presented":[177],"terms":[179],"peak":[181],"signal":[182],"noise":[184],"ratio":[185],"(PSNR),":[186],"mean":[187],"structural":[188],"similarity":[189,192],"(MSSIM),":[190],"feature":[191],"(FSIM),":[193],"computational":[195],"time":[196],"(CPU":[197],"Time)":[198],"at":[199],"different":[200],"levels":[202],"4,":[204],"6,":[205],"8,":[206],"10":[208],"each":[210],"test":[211],"image.":[212],"A":[213],"series":[214],"experiments":[216],"can":[217,228],"significantly":[218],"demonstrate":[219],"superior":[221],"performance":[222],"technique,":[226],"deal":[229],"multilevel":[231],"image":[234],"excellently.":[236]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}