{"id":"https://openalex.org/W2520263632","doi":"https://doi.org/10.1145/2967878.2967899","title":"A Comparative Study on EM Algorithms for Color-Texture Image Segmentation","display_name":"A Comparative Study on EM Algorithms for Color-Texture Image Segmentation","publication_year":2016,"publication_date":"2016-07-06","ids":{"openalex":"https://openalex.org/W2520263632","doi":"https://doi.org/10.1145/2967878.2967899","mag":"2520263632"},"language":"en","primary_location":{"id":"doi:10.1145/2967878.2967899","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2967878.2967899","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Computing Communication and Networking Technologies","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/A5055909810","display_name":"Qinpei Zhao","orcid":"https://orcid.org/0000-0002-1765-1171"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinpei Zhao","raw_affiliation_strings":["School of Software Engineering, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110404759","display_name":"Zhenyu Liao","orcid":"https://orcid.org/0000-0001-7357-0205"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Liao","raw_affiliation_strings":["School of Software Engineering, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102009687","display_name":"Jiangfeng Li","orcid":"https://orcid.org/0000-0002-1128-3259"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangfeng Li","raw_affiliation_strings":["School of Software Engineering, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101908670","display_name":"Yang Shi","orcid":"https://orcid.org/0000-0002-1065-4038"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Shi","raw_affiliation_strings":["School of Software Engineering, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05892275,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10136","display_name":"Statistical Methods and Inference","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9840999841690063,"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":0.7292971014976501},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.6919833421707153},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.6772357821464539},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.6291539669036865},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6216696500778198},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.6106598377227783},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5607765316963196},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5356862545013428},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5268774628639221},{"id":"https://openalex.org/keywords/region-growing","display_name":"Region growing","score":0.5063186883926392},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.4367738366127014},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43532028794288635},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.41068172454833984},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39722347259521484},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3306484818458557},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.23304858803749084},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08622509241104126}],"concepts":[{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.7292971014976501},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.6919833421707153},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.6772357821464539},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.6291539669036865},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6216696500778198},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.6106598377227783},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5607765316963196},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5356862545013428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5268774628639221},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.5063186883926392},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.4367738366127014},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43532028794288635},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.41068172454833984},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39722347259521484},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3306484818458557},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.23304858803749084},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08622509241104126},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2967878.2967899","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2967878.2967899","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Computing Communication and Networking Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4350908504","display_name":null,"funder_award_id":"61503286,61202382","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1560356","https://openalex.org/W1585610988","https://openalex.org/W1618045731","https://openalex.org/W1819316285","https://openalex.org/W1966129222","https://openalex.org/W1984526963","https://openalex.org/W2047555270","https://openalex.org/W2049633694","https://openalex.org/W2072634211","https://openalex.org/W2099297832","https://openalex.org/W2104019579","https://openalex.org/W2114759290","https://openalex.org/W2117853077","https://openalex.org/W2118292158","https://openalex.org/W2140136927","https://openalex.org/W2158811997","https://openalex.org/W2171096036","https://openalex.org/W2171394663","https://openalex.org/W4245883374"],"related_works":["https://openalex.org/W2204605857","https://openalex.org/W2069318476","https://openalex.org/W3196005494","https://openalex.org/W2115198604","https://openalex.org/W2162746041","https://openalex.org/W2093085045","https://openalex.org/W2377721550","https://openalex.org/W2184524617","https://openalex.org/W1996489018","https://openalex.org/W2386159816"],"abstract_inverted_index":{"Expectation-Maximization":[0],"(EM)":[1],"algorithm":[2,132,146],"has":[3],"been":[4],"thoroughly":[5],"studied":[6,149],"in":[7,38,125],"the":[8,24,59,87,99,106,113,117,126,129,135,144,151],"maximum":[9],"likelihood":[10],"estimate":[11],"of":[12,26,29,44,50,101,128,137,143],"model":[13],"parameters":[14],"for":[15,63,122],"statistical":[16],"learning.":[17],"Albeit":[18],"EM":[19,52,78,88,103,118,145],"algorithms":[20],"are":[21,32,54,120],"exploited":[22],"to":[23,41,57,133],"nature":[25],"a":[27,73,91],"variety":[28],"problems,":[30],"they":[31],"commonly":[33],"faced":[34],"with":[35],"operational":[36],"difficulty":[37],"practice,":[39],"due":[40],"its":[42],"convergence":[43],"local":[45,140],"maxima.":[46],"The":[47,139],"actual":[48],"performance":[49,136],"different":[51,77],"variants":[53,89,104,119],"seldom":[55],"evaluated":[56,98],"resolve":[58],"same":[60],"application-specific":[61],"problem,":[62],"example":[64],"image":[65,93,114,152],"segmentation.":[66],"In":[67],"this":[68],"work,":[69],"we":[70,85],"have":[71],"conducted":[72],"comparative":[74],"study":[75],"on":[76,112],"variants.":[79],"To":[80],"more":[81],"visually":[82],"compare":[83],"them,":[84],"employ":[86],"into":[90],"color-texture":[92,130],"segmentation":[94,131,153],"algorithm.":[95],"We":[96],"first":[97],"effectiveness":[100],"several":[102],"using":[105],"log-likelihood":[107],"and":[108],"Bayesian":[109],"Information":[110],"Criterion":[111],"data.":[115],"Then":[116],"used":[121],"color":[123],"quantization":[124],"framework":[127],"assess":[134],"them.":[138],"maxima":[141],"problem":[142],"is":[147],"also":[148],"by":[150],"results.":[154]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
