{"id":"https://openalex.org/W2024936415","doi":"https://doi.org/10.1109/icarcv.2012.6485387","title":"Color image segmentation using mean shift and improved spectral clustering","display_name":"Color image segmentation using mean shift and improved spectral clustering","publication_year":2012,"publication_date":"2012-12-01","ids":{"openalex":"https://openalex.org/W2024936415","doi":"https://doi.org/10.1109/icarcv.2012.6485387","mag":"2024936415"},"language":"en","primary_location":{"id":"doi:10.1109/icarcv.2012.6485387","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv.2012.6485387","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","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/A5100858919","display_name":"Yang Gui","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Gui","raw_affiliation_strings":["Department of Military AeroSpace, College of AeroSpace and Materials Engineering, National University of Defense Technology, Changsha, Hunan, China","Department of Military Aerospace, College of Aerospace and Materials Engineering, National University of Defense Technology, Changsha, Hunan, P.R. China, 410073"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Military AeroSpace, College of AeroSpace and Materials Engineering, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"Department of Military Aerospace, College of Aerospace and Materials Engineering, National University of Defense Technology, Changsha, Hunan, P.R. China, 410073","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039363991","display_name":"Xiang Bai","orcid":"https://orcid.org/0000-0002-3449-5940"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiang Bai","raw_affiliation_strings":["Beijing Institute of Tracking and Telecommunications Technology, Beijing, China","Beijing Institute of Tracking and Telecommunications Technology, Beijing, P.R. China, 100094"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Tracking and Telecommunications Technology, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Beijing Institute of Tracking and Telecommunications Technology, Beijing, P.R. China, 100094","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100414977","display_name":"Zheng Li","orcid":"https://orcid.org/0000-0002-1447-4448"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng Li","raw_affiliation_strings":["Beijing AeroSpace Long March Scientific and Technical Information Institute, Beijing, China","Beijing Aerospace Long March Scientific and Technical Information Institute, Beijing, P.R. China, 100076"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing AeroSpace Long March Scientific and Technical Information Institute, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Beijing Aerospace Long March Scientific and Technical Information Institute, Beijing, P.R. China, 100076","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078100998","display_name":"Yun Yuan","orcid":"https://orcid.org/0000-0002-8979-258X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Yuan","raw_affiliation_strings":["Department of Military AeroSpace, College of AeroSpace and Materials Engineering, National University of Defense Technology, Changsha, Hunan, China","Department of Military Aerospace, College of Aerospace and Materials Engineering, National University of Defense Technology, Changsha, Hunan, P.R. China, 410073"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Military AeroSpace, College of AeroSpace and Materials Engineering, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"Department of Military Aerospace, College of Aerospace and Materials Engineering, National University of Defense Technology, Changsha, Hunan, P.R. China, 410073","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5209,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69534338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"26","issue":null,"first_page":"1386","last_page":"1391"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9983999729156494,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9983999729156494,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9896000027656555,"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/image-segmentation","display_name":"Image segmentation","score":0.7040109038352966},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6740146279335022},{"id":"https://openalex.org/keywords/range-segmentation","display_name":"Range segmentation","score":0.6448163390159607},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6365428566932678},{"id":"https://openalex.org/keywords/mean-shift","display_name":"Mean-shift","score":0.6072945594787598},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5965522527694702},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5616337060928345},{"id":"https://openalex.org/keywords/region-growing","display_name":"Region growing","score":0.5542197823524475},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.5537089109420776},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.546377956867218},{"id":"https://openalex.org/keywords/minimum-spanning-tree-based-segmentation","display_name":"Minimum spanning tree-based segmentation","score":0.524130642414093},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.49830174446105957},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4893164336681366},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44199734926223755},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.43845832347869873},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.4192025363445282},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.41599130630493164},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3846956491470337},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3675810694694519},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.06087327003479004},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.059653908014297485}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.7040109038352966},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6740146279335022},{"id":"https://openalex.org/C67561299","wikidata":"https://www.wikidata.org/wiki/Q7292710","display_name":"Range segmentation","level":5,"score":0.6448163390159607},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6365428566932678},{"id":"https://openalex.org/C48548287","wikidata":"https://www.wikidata.org/wiki/Q6803557","display_name":"Mean-shift","level":3,"score":0.6072945594787598},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5965522527694702},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5616337060928345},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.5542197823524475},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.5537089109420776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.546377956867218},{"id":"https://openalex.org/C42314347","wikidata":"https://www.wikidata.org/wiki/Q6865488","display_name":"Minimum spanning tree-based segmentation","level":5,"score":0.524130642414093},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.49830174446105957},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4893164336681366},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44199734926223755},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.43845832347869873},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.4192025363445282},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.41599130630493164},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3846956491470337},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3675810694694519},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.06087327003479004},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.059653908014297485}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarcv.2012.6485387","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv.2012.6485387","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W150776092","https://openalex.org/W1503902529","https://openalex.org/W1637517007","https://openalex.org/W1963959122","https://openalex.org/W1991422884","https://openalex.org/W2022686119","https://openalex.org/W2039934205","https://openalex.org/W2067191022","https://openalex.org/W2097323414","https://openalex.org/W2101744728","https://openalex.org/W2116810533","https://openalex.org/W2119300483","https://openalex.org/W2121743855","https://openalex.org/W2121947440","https://openalex.org/W2122184585","https://openalex.org/W2133132416","https://openalex.org/W2136704614","https://openalex.org/W2136825928","https://openalex.org/W2139478903","https://openalex.org/W2146149474","https://openalex.org/W2153797875","https://openalex.org/W2165096258","https://openalex.org/W2165874743","https://openalex.org/W2169551590","https://openalex.org/W2220464190","https://openalex.org/W2344048381","https://openalex.org/W2351849108","https://openalex.org/W6682814531","https://openalex.org/W6684510802","https://openalex.org/W6684578312","https://openalex.org/W6689048832"],"related_works":["https://openalex.org/W2551987074","https://openalex.org/W2394279717","https://openalex.org/W2366050026","https://openalex.org/W3155984174","https://openalex.org/W2553765490","https://openalex.org/W2946366565","https://openalex.org/W4386493545","https://openalex.org/W2359699469","https://openalex.org/W1538372232","https://openalex.org/W2992988357"],"abstract_inverted_index":{"A":[0],"novel":[1],"approach":[2,25,161],"is":[3,34,54,84,92,141,162],"presented":[4],"for":[5],"color":[6,172],"image":[7,33,50,78],"segmentation.":[8,30],"By":[9],"incorporating":[10],"the":[11,23,45,62,67,70,77,95,124,131,144,159],"advantages":[12],"of":[13,56,66,120,139,158,169],"mean":[14],"shift":[15],"(MS)":[16],"segmentation":[17,53],"and":[18,28,80,154,164],"spectral":[19],"clustering":[20],"(SC)":[21],"method,":[22],"proposed":[24,160],"provides":[26],"effective":[27],"robust":[29],"Firstly,":[31],"input":[32,49],"transformed":[35],"from":[36],"a":[37,40,81,167],"pixel-based":[38],"to":[39,86,93,98,122,127,150],"region-based":[41],"model":[42],"by":[43],"using":[44,171],"MS":[46,52],"algorithm.":[47],"The":[48,89,156],"after":[51],"composed":[55],"multiple":[57],"disjoint":[58],"regions":[59,71,125],"that":[60],"preserve":[61],"desirable":[63],"discontinuity":[64],"characteristics":[65],"image.":[68],"Then":[69],"are":[72],"treated":[73],"as":[74,112],"nodes":[75,121],"in":[76,143,148],"plane":[79],"graph":[82,114],"structure":[83],"applied":[85,142],"represent":[87,123],"them.":[88],"final":[90],"step":[91],"apply":[94],"improved":[96,145],"SC":[97,146],"perform":[99],"globally":[100],"optimal":[101],"clustering.":[102],"To":[103],"avoid":[104],"some":[105],"incorrect":[106],"partitioning":[107],"when":[108],"considering":[109],"each":[110],"region":[111],"one":[113],"node,":[115],"we":[116],"assign":[117],"different":[118],"numbers":[119],"according":[126],"area":[128],"ratios":[129],"among":[130],"regions.":[132],"In":[133],"addition,":[134],"K-harmonic":[135],"means":[136],"(KHM)":[137],"instead":[138],"K-means":[140],"procedure":[147],"order":[149],"enhance":[151],"its":[152],"stability":[153],"performance.":[155],"superiority":[157],"demonstrated":[163],"examined":[165],"through":[166],"mass":[168],"experiments":[170],"images.":[173]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}