{"id":"https://openalex.org/W2096990042","doi":"https://doi.org/10.1109/cvpr.1996.517066","title":"Comparison of edge detectors: a methodology and initial study","display_name":"Comparison of edge detectors: a methodology and initial study","publication_year":1996,"publication_date":"1996-01-01","ids":{"openalex":"https://openalex.org/W2096990042","doi":"https://doi.org/10.1109/cvpr.1996.517066","mag":"2096990042"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.1996.517066","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.1996.517066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition","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/A5089510764","display_name":"Michael D. Heath","orcid":null},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"M. Heath","raw_affiliation_strings":["Computer Science & Engineering, University of South Florida, Tampa, FL, USA","Dept of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, University of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]},{"raw_affiliation_string":"Dept of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020674314","display_name":"Sudeep Sarkar","orcid":"https://orcid.org/0000-0001-7332-4207"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S. Sarkar","raw_affiliation_strings":["Computer Science & Engineering, University of South Florida, Tampa, FL, USA","Dept of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, University of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]},{"raw_affiliation_string":"Dept of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070175944","display_name":"Thomas Sanocki","orcid":"https://orcid.org/0000-0001-7608-0324"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"T. Sanocki","raw_affiliation_strings":["Department of Psycliology, University of South Florida, Tampa, FL, USA","[Department of Psycliology, University of South Florida, Tampa, FL, USA]"],"affiliations":[{"raw_affiliation_string":"Department of Psycliology, University of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]},{"raw_affiliation_string":"[Department of Psycliology, University of South Florida, Tampa, FL, USA]","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019673624","display_name":"Kevin W. Bowyer","orcid":"https://orcid.org/0000-0002-7562-4390"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"K. Bowyer","raw_affiliation_strings":["Computer Science & Engineering, University of South Florida, Tampa, FL, USA","Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, University of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]},{"raw_affiliation_string":"Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5089510764"],"corresponding_institution_ids":["https://openalex.org/I2613432"],"apc_list":null,"apc_paid":null,"fwci":5.4823,"has_fulltext":false,"cited_by_count":203,"citation_normalized_percentile":{"value":0.95886377,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"143","last_page":"148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9977999925613403,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6836771368980408},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6109908223152161},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6101588010787964},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5717735886573792},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5605916380882263},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5523421168327332},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5454259514808655},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.4763900637626648},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.46747562289237976},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.43293601274490356},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42677342891693115},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.41782164573669434},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.41772863268852234},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.41106653213500977},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33210331201553345},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3053557872772217},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2242816984653473}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6836771368980408},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6109908223152161},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6101588010787964},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5717735886573792},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5605916380882263},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5523421168327332},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5454259514808655},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.4763900637626648},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.46747562289237976},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.43293601274490356},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42677342891693115},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.41782164573669434},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.41772863268852234},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.41106653213500977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33210331201553345},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3053557872772217},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2242816984653473},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C188082640","wikidata":"https://www.wikidata.org/wiki/Q1780899","display_name":"Complementation","level":4,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.1996.517066","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.1996.517066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.45.5214","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.5214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ftp://figment.csee.usf.edu/pub/Edge_Comparison/comparison.ps.Z","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.96.9912","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.96.9912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://figment.csee.usf.edu/~sarkar/PDFs/heath-cviu.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W432921921","https://openalex.org/W1899325259","https://openalex.org/W1966992150","https://openalex.org/W1968102088","https://openalex.org/W1973494573","https://openalex.org/W1982446433","https://openalex.org/W1983164306","https://openalex.org/W1987381328","https://openalex.org/W1988199137","https://openalex.org/W2004188345","https://openalex.org/W2011109591","https://openalex.org/W2016396776","https://openalex.org/W2043854192","https://openalex.org/W2053940502","https://openalex.org/W2064887461","https://openalex.org/W2074660840","https://openalex.org/W2078085827","https://openalex.org/W2090473366","https://openalex.org/W2105954112","https://openalex.org/W2115734187","https://openalex.org/W2121961535","https://openalex.org/W2122365661","https://openalex.org/W2123295993","https://openalex.org/W2124910748","https://openalex.org/W2126742455","https://openalex.org/W2133849819","https://openalex.org/W2137693436","https://openalex.org/W2141403362","https://openalex.org/W2142117860","https://openalex.org/W2145023731","https://openalex.org/W2145475425","https://openalex.org/W2151490574","https://openalex.org/W2152866827","https://openalex.org/W2153409035","https://openalex.org/W2164507445","https://openalex.org/W2165828693","https://openalex.org/W2167882768","https://openalex.org/W2175086196","https://openalex.org/W2314731117","https://openalex.org/W4234180827","https://openalex.org/W4235387018"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2000169967","https://openalex.org/W2112883198"],"abstract_inverted_index":{"The":[0,127,168,231,258,271],"purpose":[1],"of":[2,33,51,79,91,124,143,187,201,233,260,282,285],"this":[3,110],"paper":[4,111],"is":[5,112,185,283],"to":[6,18,45,101,181,196,226,236,295],"describe":[7],"a":[8,38,98],"new":[9],"(to":[10],"computer":[11],"vision)":[12],"experimental":[13,64],"framework":[14],"which":[15,177],"allows":[16],"us":[17,44],"make":[19,46,73],"quantitative":[20,103],"comparisons":[21],"using":[22,63,223],"subjective":[23],"ratings":[24,195,225],"made":[25],"by":[26,163],"people.":[27],"This":[28,93],"approach":[29,94],"avoids":[30],"the":[31,49,59,77,89,106,122,131,138,140,160,213,276],"issue":[32],"pixel-level":[34],"ground":[35],"truth.":[36],"As":[37],"result,":[39],"it":[40],"does":[41],"not":[42],"allow":[43],"statements":[47,74],"about":[48,75],"frequency":[50],"false":[52,55],"positive":[53],"and":[54,66,154,165,189,205,248,251],"negative":[56],"errors":[57],"at":[58],"pixel":[60],"level.":[61],"Instead,":[62],"design":[65],"statistical":[67,256,261,292],"techniques":[68],"borrowed":[69],"from":[70],"Psychology,":[71],"we":[72,117,173,279],"whether":[76],"outputs":[78,90,239],"one":[80],"edge":[81,119,148,229],"detector":[82],"are":[83,174,280],"rated":[84],"statistically":[85],"significantly":[86],"higher":[87],"than":[88,222],"another.":[92],"offers":[95],"itself":[96],"as":[97],"nice":[99],"complement":[100],"signal-based":[102],"measures.":[104],"Also,":[105],"evaluation":[107],"paradigm":[108],"in":[109,115,121,156,263,275],"goal":[113],"oriented;":[114],"particular,":[116],"consider":[118],"detection":[120,149],"context":[123],"object":[125,300],"recognition.":[126],"human":[128,194,210,217,224,234],"judges":[129,235],"rate":[130,182,237],"edge,":[132],"detectors":[133],"based":[134,299],"on":[135,198,216],"how":[136],"well":[137],"capture":[139],"salient":[141],"features":[142],"real":[144],"objects.":[145],"So":[146],"far,":[147],"modules":[150],"have":[151],"been":[152,269],"designed":[153,247],"evaluated":[155],"isolation,":[157],"except":[158],"for":[159],"recent":[161],"work":[162,171,274],"Ramesh":[164],"Haralick":[166],"(1992).":[167],"only":[169,272],"prior":[170,273],"(that":[172],"aware":[175,281],"of)":[176],"also":[178,208],"uses":[179],"humans":[180],"image":[183,202,238],"algorithms":[184],"that":[186,278,284],"Reeves":[188],"Higdon":[190],"(1995).":[191],"They":[192],"use":[193,232,259],"decide":[197],"regularization":[199],"parameters":[200],"restoration.":[203],"Fram":[204],"Deutch":[206],"(1975)":[207],"used":[209,291],"subjects,":[211],"however,":[212],"focus":[214],"was":[215],"versus":[218],"machine":[219],"performance":[220,266],"rather":[221],"compare":[227,296],"different":[228],"detectors.":[230],"mist":[240],"be":[241,246],"approached":[242],"systematically.":[243],"Experiments":[244],"must":[245],"conducted":[249],"carefully,":[250],"results":[252],"interpreted":[253],"with":[254],"appropriate":[255],"tools.":[257],"analysis":[262],"vision":[264],"system":[265],"characterization":[267],"has":[268],"rare.":[270],"area":[277],"Nair":[286],"et":[287],"al.":[288],"(1995),":[289],"who":[290],"ranking":[293],"procedures":[294],"neural":[297],"network":[298],"recognition":[301],"systems.":[302]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":11},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":10},{"year":2013,"cited_by_count":13},{"year":2012,"cited_by_count":15}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}