{"id":"https://openalex.org/W2162143504","doi":"https://doi.org/10.1109/isspa.2003.1224805","title":"Detecting eyes in digital images","display_name":"Detecting eyes in digital images","publication_year":2003,"publication_date":"2003-01-01","ids":{"openalex":"https://openalex.org/W2162143504","doi":"https://doi.org/10.1109/isspa.2003.1224805","mag":"2162143504"},"language":"en","primary_location":{"id":"doi:10.1109/isspa.2003.1224805","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspa.2003.1224805","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings.","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/A5053470224","display_name":"D. Robert Iskander","orcid":"https://orcid.org/0000-0002-5962-6206"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"D.R. Iskander","raw_affiliation_strings":["Electronics and Signal Processing Group, School of Engineering, Griffith University, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Signal Processing Group, School of Engineering, Griffith University, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061546998","display_name":"Siegfried Mioschek","orcid":null},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"S. Mioschek","raw_affiliation_strings":["Electronics and Signal Processing Group, School of Engineering, Griffith University, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Signal Processing Group, School of Engineering, Griffith University, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058063746","display_name":"Martin Trunk","orcid":null},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"M. Trunk","raw_affiliation_strings":["Electronics and Signal Processing Group, School of Engineering, Griffith University, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Signal Processing Group, School of Engineering, Griffith University, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064386017","display_name":"Wolfgang Werth","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"W. Werth","raw_affiliation_strings":["School of Electronics, Carinthia Tech Institute, Villach, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics, Carinthia Tech Institute, Villach, Austria","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8086,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76121599,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"21","last_page":"24 vol.2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9991000294685364,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9991000294685364,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9800000190734863,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9793000221252441,"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-vision","display_name":"Computer vision","score":0.7665377855300903},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7635889649391174},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7539157867431641},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.7098815441131592},{"id":"https://openalex.org/keywords/hough-transform","display_name":"Hough transform","score":0.579655110836029},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5189954042434692},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5163477659225464},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.5150987505912781},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4872783422470093},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.4653611481189728},{"id":"https://openalex.org/keywords/pupil","display_name":"Pupil","score":0.4251036047935486},{"id":"https://openalex.org/keywords/reflection","display_name":"Reflection (computer programming)","score":0.41867464780807495},{"id":"https://openalex.org/keywords/iris","display_name":"IRIS (biosensor)","score":0.41053470969200134},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.40386784076690674},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21410095691680908},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.18930602073669434},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1333397626876831},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.08011487126350403}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7665377855300903},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7635889649391174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7539157867431641},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.7098815441131592},{"id":"https://openalex.org/C200518788","wikidata":"https://www.wikidata.org/wiki/Q195076","display_name":"Hough transform","level":3,"score":0.579655110836029},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5189954042434692},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5163477659225464},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5150987505912781},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4872783422470093},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.4653611481189728},{"id":"https://openalex.org/C2777394604","wikidata":"https://www.wikidata.org/wiki/Q173318","display_name":"Pupil","level":2,"score":0.4251036047935486},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.41867464780807495},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.41053470969200134},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.40386784076690674},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21410095691680908},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.18930602073669434},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1333397626876831},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.08011487126350403},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"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:10.1109/isspa.2003.1224805","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspa.2003.1224805","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8600000143051147}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1977804219","https://openalex.org/W1990049419","https://openalex.org/W2002100650","https://openalex.org/W2028115599","https://openalex.org/W2060321377","https://openalex.org/W2105025080","https://openalex.org/W2128654298","https://openalex.org/W2147824893","https://openalex.org/W2153360856","https://openalex.org/W2157406231","https://openalex.org/W2172160147"],"related_works":["https://openalex.org/W3034835805","https://openalex.org/W2065648684","https://openalex.org/W2113052720","https://openalex.org/W2799624451","https://openalex.org/W2009383287","https://openalex.org/W1987236632","https://openalex.org/W2042914788","https://openalex.org/W2182190754","https://openalex.org/W2398428658","https://openalex.org/W4321264664"],"abstract_inverted_index":{"Detecting":[0],"eyes":[1],"in":[2,6,48,57,64,88,163,180],"digital":[3,89],"images":[4,49],"taken":[5],"a":[7,15,55,76,99,117,164],"variety":[8,166],"of":[9,98,106,112,143,167,171],"natural":[10],"lighting":[11],"conditions":[12],"is":[13,94,182],"not":[14,40,71],"straightforward":[16],"task.":[17],"Great":[18],"difficulties":[19],"are":[20,70],"experienced":[21],"when":[22],"one":[23],"attempts":[24],"to":[25,38,43,149,174],"employ":[26],"traditional":[27],"methods":[28],"such":[29],"as":[30],"the":[31,45,58,107,113,133,137,146,161,172],"Radon":[32],"or":[33,54,60],"Hough":[34],"transforms.":[35],"They":[36],"appear":[37],"be":[39,150],"robust":[41,152],"enough":[42],"perform":[44],"detection":[46],"task":[47],"that":[50,132],"include":[51],"blur,":[52],"speckles,":[53],"reflection":[56],"pupil":[59],"iris":[61],"areas.":[62],"Also,":[63,145],"some":[65],"practical":[66],"applications":[67],"these":[68],"techniques":[69],"computationally":[72],"efficient.":[73],"We":[74],"propose":[75],"simple":[77],"quadruple":[78],"axis":[79],"spatial-domain-based":[80],"symmetry":[81],"indicator":[82],"for":[83,102,140],"detecting":[84],"circularly":[85],"symmetric":[86],"objects":[87],"images.":[90,127,168],"The":[91,110],"proposed":[92,114,134],"detector":[93,121,139,173],"an":[95],"inherent":[96],"part":[97],"larger":[100],"system":[101],"estimating":[103],"2D":[104],"characteristics":[105],"human":[108],"eye.":[109],"efficacy":[111],"technique":[115],"versus":[116],"frequency":[118,155],"domain":[119,156],"energy":[120],"has":[122,129],"been":[123,130],"evaluated":[124],"using":[125],"artificial":[126],"It":[128],"shown":[131],"method":[135,147],"outperforms":[136],"energy-based":[138],"moderate":[141],"levels":[142],"noise.":[144],"appears":[148],"more":[151],"than":[153],"its":[154],"counterpart":[157],"and":[158,177],"correctly":[159],"detects":[160],"eye":[162],"wide":[165],"An":[169],"application":[170],"clinical":[175],"assessment":[176],"patient":[178],"diagnosis":[179],"optometry":[181],"provided.":[183]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}