{"id":"https://openalex.org/W2901830806","doi":"https://doi.org/10.1109/ic3.2018.8530568","title":"cKGSA Based Fuzzy Clustering Method for Image Segmentation of RGB-D Images","display_name":"cKGSA Based Fuzzy Clustering Method for Image Segmentation of RGB-D Images","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2901830806","doi":"https://doi.org/10.1109/ic3.2018.8530568","mag":"2901830806"},"language":"en","primary_location":{"id":"doi:10.1109/ic3.2018.8530568","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic3.2018.8530568","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","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/A5011200124","display_name":"Himanshu Mittal","orcid":"https://orcid.org/0000-0003-4127-7092"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Himanshu Mittal","raw_affiliation_strings":["Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India","institution_ids":["https://openalex.org/I154970844"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015706894","display_name":"Mukesh Saraswat","orcid":"https://orcid.org/0000-0002-3427-9105"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mukesh Saraswat","raw_affiliation_strings":["Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India","institution_ids":["https://openalex.org/I154970844"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5011200124"],"corresponding_institution_ids":["https://openalex.org/I154970844"],"apc_list":null,"apc_paid":null,"fwci":1.7012,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.8890813,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"2018","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9983000159263611,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9983000159263611,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9973999857902527,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9962000250816345,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.783523440361023},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.7014187574386597},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6778975129127502},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.6244210004806519},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5842811465263367},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5835610032081604},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5811192393302917},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5588722825050354},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5270593166351318},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5259045362472534},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.49831080436706543},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.4975169003009796}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.783523440361023},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.7014187574386597},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6778975129127502},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.6244210004806519},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5842811465263367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5835610032081604},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5811192393302917},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5588722825050354},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5270593166351318},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5259045362472534},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.49831080436706543},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.4975169003009796}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ic3.2018.8530568","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic3.2018.8530568","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Eleventh International Conference on Contemporary Computing (IC3)","raw_type":"proceedings-article"},{"id":"mag:3176051250","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201802229420101706","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1595159159","https://openalex.org/W1596914020","https://openalex.org/W1968674232","https://openalex.org/W2004239997","https://openalex.org/W2010975286","https://openalex.org/W2011430131","https://openalex.org/W2022637272","https://openalex.org/W2053922829","https://openalex.org/W2066813062","https://openalex.org/W2072955302","https://openalex.org/W2076408892","https://openalex.org/W2090171185","https://openalex.org/W2124475834","https://openalex.org/W2125186487","https://openalex.org/W2141845743","https://openalex.org/W2145617041","https://openalex.org/W2167638481","https://openalex.org/W2276299717","https://openalex.org/W2296672305","https://openalex.org/W2402846924","https://openalex.org/W2460884160","https://openalex.org/W2548986579","https://openalex.org/W2560183395","https://openalex.org/W2569298377","https://openalex.org/W2593949166","https://openalex.org/W2594056497","https://openalex.org/W2597453252","https://openalex.org/W2599356748","https://openalex.org/W2602538967","https://openalex.org/W2752633099","https://openalex.org/W2765421624","https://openalex.org/W2765633573","https://openalex.org/W2787693233","https://openalex.org/W2787710908","https://openalex.org/W2790510783","https://openalex.org/W2900915272","https://openalex.org/W4300106150","https://openalex.org/W6605121731","https://openalex.org/W6653423199","https://openalex.org/W6666899075","https://openalex.org/W6672818256","https://openalex.org/W6682642761","https://openalex.org/W6697637822","https://openalex.org/W6729293419","https://openalex.org/W6743888193"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W2055202857","https://openalex.org/W4205800335","https://openalex.org/W2371519352","https://openalex.org/W2386644571","https://openalex.org/W2372421320","https://openalex.org/W2901890255"],"abstract_inverted_index":{"With":[0],"the":[1,52,72,76,80,92,102,116,139,153,157,163],"introduction":[2],"of":[3,18,138,145,156],"low-cost":[4],"depth":[5,110],"image":[6,9,26,39,106],"sensors,":[7],"reliable":[8],"segmentation":[10,27,40,81,94,154],"within":[11],"RGB-D":[12,38,104],"images":[13],"is":[14,99,141,160],"an":[15],"ambitious":[16],"goal":[17],"computer":[19],"vision.":[20],"However,":[21],"in":[22,143],"a":[23,30,36],"cluttered":[24],"scene,":[25],"has":[28],"become":[29],"challenging":[31],"problem.":[32],"This":[33],"paper":[34],"presents":[35],"novel":[37],"method,":[41],"chaotic":[42],"kbest":[43],"gravitational":[44,129],"search":[45,130],"algorithm":[46],"based":[47],"fuzzy":[48,56,121,132],"clustering":[49,57,122,126],"(cKGSA-FC).":[50],"First,":[51],"proposed":[53,73,97,158],"method":[54,74,86,98,159],"performs":[55],"using":[58],"cKGSA":[59],"on":[60,87,101],"different":[61,88],"parameters":[62],"and":[63,113,134,147],"feature":[64],"subsets":[65],"to":[66,90],"obtain":[67],"multiple":[68,77],"optimal":[69],"clusters.":[70],"Next,":[71],"combines":[75],"clusters":[78],"through":[79,123],"by":[82,119],"aggregating":[83],"superpixels":[84],"(SAS)":[85],"combinations":[89],"generate":[91],"final":[93],"result.":[95],"The":[96,136],"evaluated":[100],"standard":[103],"indoor":[105],"dataset":[107],"namely;":[108,128],"NYU":[109],"v2":[111],"(NYUD2)":[112],"compared":[114,164],"with":[115],"results":[117,140,150],"obtained":[118],"performing":[120],"three":[124],"existing":[125],"methods":[127],"algorithm,":[131],"c-means,":[133],"kmeans.":[135],"evaluation":[137],"done":[142],"terms":[144],"qualitative":[146],"quantitative.":[148],"Experimental":[149],"confirm":[151],"that":[152],"quality":[155],"superior":[161],"than":[162],"methods.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}