{"id":"https://openalex.org/W1969785753","doi":"https://doi.org/10.1109/iceee.2014.6978260","title":"Maximum likelihood thresholding algorithm based on four-parameter gamma distributions","display_name":"Maximum likelihood thresholding algorithm based on four-parameter gamma distributions","publication_year":2014,"publication_date":"2014-09-01","ids":{"openalex":"https://openalex.org/W1969785753","doi":"https://doi.org/10.1109/iceee.2014.6978260","mag":"1969785753"},"language":"en","primary_location":{"id":"doi:10.1109/iceee.2014.6978260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceee.2014.6978260","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","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/A5047537744","display_name":"Peter De-Ford","orcid":null},"institutions":[{"id":"https://openalex.org/I31944674","display_name":"Universidad de Costa Rica","ror":"https://ror.org/02yzgww51","country_code":"CR","type":"education","lineage":["https://openalex.org/I31944674"]}],"countries":["CR"],"is_corresponding":true,"raw_author_name":"Peter De-Ford","raw_affiliation_strings":["Image Processing and Computer Vision Research Laboratory (IPCV-LAB), Universidad de Costa Rica, San Jos\u00e9, Costa Rica","Image Processing and Computer Vision Research Laboratory (IPCV-LAB) Escuela de Ingenier\u00eda El\u00e9ctrica, Universidad de Costa Rica, Apartado Postal 11501-2060 UCR, San Jos\u00e9, Costa Rica"],"affiliations":[{"raw_affiliation_string":"Image Processing and Computer Vision Research Laboratory (IPCV-LAB), Universidad de Costa Rica, San Jos\u00e9, Costa Rica","institution_ids":["https://openalex.org/I31944674"]},{"raw_affiliation_string":"Image Processing and Computer Vision Research Laboratory (IPCV-LAB) Escuela de Ingenier\u00eda El\u00e9ctrica, Universidad de Costa Rica, Apartado Postal 11501-2060 UCR, San Jos\u00e9, Costa Rica","institution_ids":["https://openalex.org/I31944674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109048428","display_name":"Geovanni Mart\u00ednez","orcid":null},"institutions":[{"id":"https://openalex.org/I31944674","display_name":"Universidad de Costa Rica","ror":"https://ror.org/02yzgww51","country_code":"CR","type":"education","lineage":["https://openalex.org/I31944674"]}],"countries":["CR"],"is_corresponding":false,"raw_author_name":"Geovanni Martinez","raw_affiliation_strings":["Image Processing and Computer Vision Research Laboratory (IPCV-LAB), Universidad de Costa Rica, San Jos\u00e9, Costa Rica","Image Processing and Computer Vision Research Laboratory (IPCV-LAB) Escuela de Ingenier\u00eda El\u00e9ctrica, Universidad de Costa Rica, Apartado Postal 11501-2060 UCR, San Jos\u00e9, Costa Rica"],"affiliations":[{"raw_affiliation_string":"Image Processing and Computer Vision Research Laboratory (IPCV-LAB), Universidad de Costa Rica, San Jos\u00e9, Costa Rica","institution_ids":["https://openalex.org/I31944674"]},{"raw_affiliation_string":"Image Processing and Computer Vision Research Laboratory (IPCV-LAB) Escuela de Ingenier\u00eda El\u00e9ctrica, Universidad de Costa Rica, Apartado Postal 11501-2060 UCR, San Jos\u00e9, Costa Rica","institution_ids":["https://openalex.org/I31944674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047537744"],"corresponding_institution_ids":["https://openalex.org/I31944674"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.04946267,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"13","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9997000098228455,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9997000098228455,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9976000189781189,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9965000152587891,"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/thresholding","display_name":"Thresholding","score":0.8397537469863892},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6112425923347473},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.5640236735343933},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5549778342247009},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.5335372686386108},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5308293700218201},{"id":"https://openalex.org/keywords/gamma-distribution","display_name":"Gamma distribution","score":0.5255804657936096},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5246296525001526},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5191173553466797},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5159376263618469},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5071878433227539},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.49298402667045593},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47752442955970764},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4428614377975464},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.41805338859558105},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.33580121397972107},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3103552460670471},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10278230905532837}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.8397537469863892},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6112425923347473},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5640236735343933},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5549778342247009},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.5335372686386108},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5308293700218201},{"id":"https://openalex.org/C149717495","wikidata":"https://www.wikidata.org/wiki/Q117806","display_name":"Gamma distribution","level":2,"score":0.5255804657936096},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5246296525001526},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5191173553466797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5159376263618469},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5071878433227539},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.49298402667045593},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47752442955970764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4428614377975464},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.41805338859558105},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.33580121397972107},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3103552460670471},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10278230905532837},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iceee.2014.6978260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceee.2014.6978260","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","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":37,"referenced_works":["https://openalex.org/W249231694","https://openalex.org/W1507322379","https://openalex.org/W1584308190","https://openalex.org/W1968204363","https://openalex.org/W1972544340","https://openalex.org/W1991588369","https://openalex.org/W1993852465","https://openalex.org/W2006218390","https://openalex.org/W2008633284","https://openalex.org/W2014068770","https://openalex.org/W2027091505","https://openalex.org/W2029235040","https://openalex.org/W2032558130","https://openalex.org/W2037369677","https://openalex.org/W2054137409","https://openalex.org/W2056612043","https://openalex.org/W2066952349","https://openalex.org/W2071481167","https://openalex.org/W2073774685","https://openalex.org/W2081401350","https://openalex.org/W2092743072","https://openalex.org/W2099552778","https://openalex.org/W2103109234","https://openalex.org/W2119249988","https://openalex.org/W2122942014","https://openalex.org/W2133003941","https://openalex.org/W2133059825","https://openalex.org/W2170969940","https://openalex.org/W2317680938","https://openalex.org/W2330254613","https://openalex.org/W2333131589","https://openalex.org/W2467186424","https://openalex.org/W6609457049","https://openalex.org/W6630348417","https://openalex.org/W6673650252","https://openalex.org/W6680096826","https://openalex.org/W6780645547"],"related_works":["https://openalex.org/W1993852465","https://openalex.org/W2013921918","https://openalex.org/W2019724159","https://openalex.org/W4280508323","https://openalex.org/W2149766606","https://openalex.org/W2371672232","https://openalex.org/W3151346708","https://openalex.org/W2397376809","https://openalex.org/W2540019423","https://openalex.org/W2120595071"],"abstract_inverted_index":{"In":[0],"this":[1],"contribution,":[2],"we":[3],"present":[4],"a":[5,30,35,54,120],"segmentation":[6],"algorithm":[7,81],"based":[8],"on":[9],"thresholding":[10],"to":[11,58,73,127],"subdivide":[12],"an":[13,113],"intensity":[14,37],"image":[15],"in":[16,83,91,98,112],"the":[17,45,64,79,88,92,116],"regions":[18],"of":[19,44,47,63,66,107,115,122],"object":[20],"and":[21,105],"background.":[22],"The":[23,102],"optimal":[24],"threshold":[25],"is":[26,82],"found":[27,90],"by":[28,119],"maximizing":[29],"likelihood":[31,109],"function":[32,40,110],"derived":[33],"from":[34,124],"novel":[36],"probability":[38],"density":[39],"model,":[41],"which":[42],"consists":[43],"sum":[46,65],"two":[48,67],"weighted":[49,68],"four-parameter":[50],"gamma":[51],"distributions,":[52],"as":[53],"more":[55],"flexible":[56],"alternative":[57],"currently":[59],"used":[60],"models":[61],"consisting":[62],"two-parameter":[69],"Gaussian":[70],"distributions.":[71],"According":[72],"our":[74],"experiments":[75],"with":[76],"132":[77],"images,":[78],"proposed":[80],"average":[84],"slightly":[85],"better":[86],"than":[87],"best":[89],"scientific":[93],"literature,":[94],"performing":[95],"particularly":[96],"good":[97],"low":[99],"contrast":[100],"images.":[101],"additional":[103],"parameters":[104],"complexity":[106],"its":[108],"resulted":[111],"increase":[114],"processing":[117],"time":[118],"factor":[121],"3,":[123],"0.003":[125],"sec/image":[126],"0.009":[128],"sec/image.":[129]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
