{"id":"https://openalex.org/W1970651031","doi":"https://doi.org/10.4304/jmm.9.8.1024-1031","title":"Color Image Segmentation Method Based on Improved Spectral Clustering Algorithm","display_name":"Color Image Segmentation Method Based on Improved Spectral Clustering Algorithm","publication_year":2014,"publication_date":"2014-08-22","ids":{"openalex":"https://openalex.org/W1970651031","doi":"https://doi.org/10.4304/jmm.9.8.1024-1031","mag":"1970651031"},"language":"en","primary_location":{"id":"doi:10.4304/jmm.9.8.1024-1031","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jmm.9.8.1024-1031","pdf_url":null,"source":{"id":"https://openalex.org/S16006927","display_name":"Journal of Multimedia","issn_l":"1796-2048","issn":["1796-2048"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Multimedia","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/A5102994390","display_name":"Qin Dong","orcid":"https://orcid.org/0000-0002-7236-1994"},"institutions":[{"id":"https://openalex.org/I4210157719","display_name":"Yancheng Institute of Technology","ror":"https://ror.org/04y8njc86","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210157719"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dong Qin","raw_affiliation_strings":["Yancheng Institute of Technology, Yan Cheng"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yancheng Institute of Technology, Yan Cheng","institution_ids":["https://openalex.org/I4210157719"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5102994390"],"corresponding_institution_ids":["https://openalex.org/I4210157719"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10128599,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":"8","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9945999979972839,"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":0.9945999979972839,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9861000180244446,"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/computer-science","display_name":"Computer science","score":0.7409906387329102},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6300573945045471},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.610444188117981},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.5298753976821899},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5125465393066406},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5082373023033142},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5006964206695557},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48424527049064636},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46350353956222534},{"id":"https://openalex.org/keywords/region-growing","display_name":"Region growing","score":0.4553835690021515},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4522670805454254},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.428724080324173},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3481346368789673}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7409906387329102},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6300573945045471},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.610444188117981},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.5298753976821899},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5125465393066406},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5082373023033142},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5006964206695557},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48424527049064636},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46350353956222534},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.4553835690021515},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4522670805454254},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.428724080324173},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3481346368789673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.4304/jmm.9.8.1024-1031","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jmm.9.8.1024-1031","pdf_url":null,"source":{"id":"https://openalex.org/S16006927","display_name":"Journal of Multimedia","issn_l":"1796-2048","issn":["1796-2048"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W218592382","https://openalex.org/W1965236874","https://openalex.org/W2048288184","https://openalex.org/W2052029481","https://openalex.org/W2068132316","https://openalex.org/W2098777834","https://openalex.org/W2107208924","https://openalex.org/W2121947440","https://openalex.org/W2130851950","https://openalex.org/W2132914434","https://openalex.org/W2181519276","https://openalex.org/W2358776684","https://openalex.org/W2378263538","https://openalex.org/W2494504357","https://openalex.org/W2568454700","https://openalex.org/W3140939614","https://openalex.org/W4255793874","https://openalex.org/W6608761777","https://openalex.org/W6663821255","https://openalex.org/W6731700973"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2394279717","https://openalex.org/W2551987074","https://openalex.org/W2364730859","https://openalex.org/W2386644571","https://openalex.org/W2185902295","https://openalex.org/W2055202857","https://openalex.org/W2103507220","https://openalex.org/W2372421320","https://openalex.org/W4313052709"],"abstract_inverted_index":{"Contraposing":[0],"to":[1,21,56,86,102,116,152,156],"the":[2,12,40,64,71,77,104,127,135,142,165],"features":[3],"of":[4,10,16,42,47,76,95,129,144],"image":[5,26,133],"data":[6,97,115],"with":[7,30],"high":[8],"sparsity":[9],"and":[11,35,45,98,120,132,154,161],"problems":[13],"on":[14],"determination":[15],"clustering":[17,49,74,105,122,147],"numbers,":[18],"we":[19,51,84],"try":[20,85],"put":[22],"forward":[23],"an":[24],"color":[25],"segmentation":[27],"algorithm,":[28],"combined":[29],"semi-supervised":[31,100],"machine":[32],"learning":[33],"technology":[34],"spectral":[36,48,146],"graph":[37],"theory.":[38],"By":[39,126],"research":[41],"related":[43],"theories":[44],"methods":[46],"algorithms,":[50],"introduce":[52],"information":[53,90],"entropy":[54],"conception":[55],"design":[57],"a":[58],"method":[59],"which":[60,149],"can":[61],"automatically":[62],"optimize":[63],"scale":[65,78],"parameter":[66,79],"value.":[67],"So":[68],"it":[69],"avoids":[70],"unstability":[72],"in":[73,92,164],"result":[75],"input":[80],"manually.":[81],"In":[82],"addition,":[83],"excavate":[87],"available":[88],"priori":[89],"existing":[91],"large":[93],"number":[94],"non-generic":[96],"apply":[99],"algorithm":[101,139],"improve":[103],"performance":[106],"for":[107],"rare":[108],"class.":[109],"We":[110],"also":[111,162],"use":[112],"added":[113],"tag":[114],"compute":[117],"similar":[118],"matrix":[119],"perform":[121],"through":[123],"FKCM":[124],"algorithms.":[125],"simulation":[128],"standard":[130],"dataset":[131],"segmentation,":[134],"experiments":[136],"demonstrate":[137],"our":[138],"has":[140],"overcome":[141],"defects":[143],"traditional":[145],"methods,":[148],"are":[150],"sensitive":[151],"outliers":[153],"easy":[155],"fall":[157],"into":[158],"local":[159],"optimum,":[160],"poor":[163],"convergence":[166],"rate":[167]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}