{"id":"https://openalex.org/W2050167119","doi":"https://doi.org/10.1117/1.2762250","title":"New benchmark for image segmentation evaluation","display_name":"New benchmark for image segmentation evaluation","publication_year":2007,"publication_date":"2007-07-01","ids":{"openalex":"https://openalex.org/W2050167119","doi":"https://doi.org/10.1117/1.2762250","mag":"2050167119"},"language":"en","primary_location":{"id":"doi:10.1117/1.2762250","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.2762250","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","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":null,"display_name":"Song Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]},{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Song Wang","raw_affiliation_strings":["Univ. of South Carolina (United States)","Virginia Tech, Department of Electrical and Computer Engineering, Blacksburg, Virginia 24061"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of South Carolina (United States)","institution_ids":["https://openalex.org/I155781252"]},{"raw_affiliation_string":"Virginia Tech, Department of Electrical and Computer Engineering, Blacksburg, Virginia 24061","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155781252","https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":4.442,"has_fulltext":false,"cited_by_count":112,"citation_normalized_percentile":{"value":0.93960069,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"16","issue":"3","first_page":"033011","last_page":"033011"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9988999962806702,"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/segmentation","display_name":"Segmentation","score":0.7517721652984619},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7126391530036926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7034903764724731},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6812044382095337},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6741483211517334},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.6420713663101196},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5966732501983643},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5686647295951843},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.4778725206851959},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47451916337013245},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42705249786376953},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.41825851798057556}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7517721652984619},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7126391530036926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7034903764724731},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6812044382095337},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6741483211517334},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.6420713663101196},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5966732501983643},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5686647295951843},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.4778725206851959},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47451916337013245},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42705249786376953},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.41825851798057556},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/1.2762250","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.2762250","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.131.3452","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.3452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.sc.edu/~songwang/document/jei07.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.4399999976158142,"display_name":"Life in Land"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310846","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W151895561","https://openalex.org/W1494159083","https://openalex.org/W1498238238","https://openalex.org/W1499635939","https://openalex.org/W1522196789","https://openalex.org/W1537766404","https://openalex.org/W1807662885","https://openalex.org/W1972544340","https://openalex.org/W1979432452","https://openalex.org/W1981710537","https://openalex.org/W1999478155","https://openalex.org/W2021744742","https://openalex.org/W2037563221","https://openalex.org/W2051084846","https://openalex.org/W2054113582","https://openalex.org/W2067191022","https://openalex.org/W2071875816","https://openalex.org/W2074642454","https://openalex.org/W2084684686","https://openalex.org/W2091867141","https://openalex.org/W2094703873","https://openalex.org/W2096680859","https://openalex.org/W2105414067","https://openalex.org/W2107290706","https://openalex.org/W2109103633","https://openalex.org/W2109407305","https://openalex.org/W2113089599","https://openalex.org/W2117193984","https://openalex.org/W2121927366","https://openalex.org/W2121947440","https://openalex.org/W2124260943","https://openalex.org/W2125313748","https://openalex.org/W2128356031","https://openalex.org/W2135705692","https://openalex.org/W2136962287","https://openalex.org/W2137063708","https://openalex.org/W2145433796","https://openalex.org/W2479500547","https://openalex.org/W2505399031","https://openalex.org/W2998023265","https://openalex.org/W3100816363"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2185902295","https://openalex.org/W2945274617","https://openalex.org/W2372421320","https://openalex.org/W2057775483","https://openalex.org/W2041871225","https://openalex.org/W2386644571","https://openalex.org/W2387793296","https://openalex.org/W1558398159","https://openalex.org/W2118381968"],"abstract_inverted_index":{"Image":[0],"segmentation":[1,19,37,72,171],"and":[2,28,36,163,187],"its":[3],"performance":[4,166],"evaluation":[5,20,47,53],"are":[6,139],"very":[7],"difficult":[8],"but":[9,112],"important":[10,130],"problems":[11],"in":[12,18,48],"computer":[13],"vision.":[14],"A":[15],"major":[16],"challenge":[17],"comes":[21],"from":[22,84],"the":[23,33,46,52,85,107,165,174,177,180,184,188],"fundamental":[24],"conflict":[25],"between":[26],"generality":[27],"objectivity:":[29],"For":[30],"general-purpose":[31],"segmentation,":[32],"ground":[34],"truth":[35],"accuracy":[38],"may":[39,55],"not":[40,56,97,140],"be":[41,57],"well":[42],"defined,":[43],"while":[44],"embedding":[45],"a":[49,64,80,88,100,124,145],"specific":[50],"application,":[51],"results":[54],"extensible":[58],"to":[59,67,75,78,117,127,142,161],"other":[60],"applications.":[61],"We":[62,121,157],"present":[63,123],"new":[65],"benchmark":[66,160],"evaluate":[68,162],"five":[69],"different":[70],"image":[71,170],"methods":[73,138],"according":[74],"their":[76],"capability":[77],"separate":[79],"perceptually":[81],"salient":[82,147,155],"structure":[83],"background":[86],"with":[87],"relatively":[89],"small":[90],"number":[91],"of":[92,103,109,167],"segments.":[93],"This":[94],"way,":[95],"we":[96],"only":[98],"find":[99],"large":[101],"variety":[102],"images":[104,152],"that":[105],"satisfy":[106],"requirement":[108],"good":[110,119],"generality,":[111],"also":[113,122],"construct":[114],"ground-truth":[115],"segmentations":[116],"achieve":[118],"objectivity.":[120],"special":[125],"strategy":[126],"address":[128],"two":[129],"issues":[131],"underlying":[132],"this":[133,159],"benchmark:":[134],"(1)":[135],"most":[136],"image-segmentation":[137],"developed":[141],"directly":[143],"extract":[144],"single":[146],"structure;":[148],"(2)":[149],"many":[150],"real":[151],"have":[153],"multiple":[154],"structures.":[156],"apply":[158],"compare":[164],"several":[168],"state-of-the-art":[169],"methods,":[172],"including":[173],"normalized-cut":[175],"method,":[176,179,183,186],"watershed":[178],"efficient":[181],"graph-based":[182],"mean-shift":[185],"ratio-cut":[189],"method.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":11},{"year":2012,"cited_by_count":9}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}
