{"id":"https://openalex.org/W7154712862","doi":"https://doi.org/10.3390/computers15040253","title":"Robust Iris Segmentation with Deep CNNs for Detecting Fully or Nearly Closed Eyes in Non-Ideal Biometric Systems","display_name":"Robust Iris Segmentation with Deep CNNs for Detecting Fully or Nearly Closed Eyes in Non-Ideal Biometric Systems","publication_year":2026,"publication_date":"2026-04-17","ids":{"openalex":"https://openalex.org/W7154712862","doi":"https://doi.org/10.3390/computers15040253"},"language":"en","primary_location":{"id":"doi:10.3390/computers15040253","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers15040253","pdf_url":"https://www.mdpi.com/2073-431X/15/4/253/pdf?version=1776428074","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-431X/15/4/253/pdf?version=1776428074","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087649556","display_name":"Farmanullah Jan","orcid":"https://orcid.org/0000-0002-9118-3652"},"institutions":[{"id":"https://openalex.org/I76571253","display_name":"Imam Abdulrahman Bin Faisal University","ror":"https://ror.org/038cy8j79","country_code":"SA","type":"education","lineage":["https://openalex.org/I76571253"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Farmanullah Jan","raw_affiliation_strings":["Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-9118-3652","affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia","institution_ids":["https://openalex.org/I76571253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5087649556"],"corresponding_institution_ids":["https://openalex.org/I76571253"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.53050913,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":"4","first_page":"253","last_page":"253"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.98089998960495,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10828","display_name":"Biometric Identification and Security","score":0.98089998960495,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11438","display_name":"Retinal Imaging and Analysis","score":0.006300000008195639,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.0012000000569969416,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/biometrics","display_name":"Biometrics","score":0.661300003528595},{"id":"https://openalex.org/keywords/iris","display_name":"IRIS (biosensor)","score":0.6291999816894531},{"id":"https://openalex.org/keywords/iris-recognition","display_name":"Iris recognition","score":0.6244000196456909},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6223000288009644},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6140000224113464},{"id":"https://openalex.org/keywords/hough-transform","display_name":"Hough transform","score":0.5806000232696533},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5699999928474426},{"id":"https://openalex.org/keywords/specular-highlight","display_name":"Specular highlight","score":0.4350999891757965},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4235999882221222}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8123999834060669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.765500009059906},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.661300003528595},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6342999935150146},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.6291999816894531},{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.6244000196456909},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6223000288009644},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6140000224113464},{"id":"https://openalex.org/C200518788","wikidata":"https://www.wikidata.org/wiki/Q195076","display_name":"Hough transform","level":3,"score":0.5806000232696533},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5699999928474426},{"id":"https://openalex.org/C50045419","wikidata":"https://www.wikidata.org/wiki/Q7575328","display_name":"Specular highlight","level":3,"score":0.4350999891757965},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4235999882221222},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.41609999537467957},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.37549999356269836},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3718000054359436},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.358599990606308},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34610000252723694},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.3433000147342682},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C14705441","wikidata":"https://www.wikidata.org/wiki/Q597183","display_name":"Canny edge detector","level":5,"score":0.29679998755455017},{"id":"https://openalex.org/C17866373","wikidata":"https://www.wikidata.org/wiki/Q5437042","display_name":"Fast marching method","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.26080000400543213},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/computers15040253","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers15040253","pdf_url":"https://www.mdpi.com/2073-431X/15/4/253/pdf?version=1776428074","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8a566549fc454c3f880f20bfd8b4ac90","is_oa":true,"landing_page_url":"https://doaj.org/article/8a566549fc454c3f880f20bfd8b4ac90","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computers, Vol 15, Iss 4, p 253 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/computers15040253","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers15040253","pdf_url":"https://www.mdpi.com/2073-431X/15/4/253/pdf?version=1776428074","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310002","display_name":"Universidade da Beira Interior","ror":"https://ror.org/03nf36p02"},{"id":"https://openalex.org/F4320313202","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320324473","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7154712862.pdf","grobid_xml":"https://content.openalex.org/works/W7154712862.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,122],"study":[1,36],"proposes":[2],"a":[3,38,73,141],"robust":[4],"hybrid":[5],"framework":[6],"for":[7,45,179],"iris":[8,81,103],"segmentation":[9,169],"in":[10,183],"covert":[11],"biometric":[12,181],"systems,":[13],"specifically":[14],"addressing":[15],"the":[16,29,84,88,117,176],"challenge":[17],"of":[18,31,63,77,157],"non-ideal":[19],"images":[20],"featuring":[21],"fully":[22,162],"or":[23,161],"nearly":[24,160],"closed":[25,163],"eyes.":[26,164],"To":[27],"overcome":[28],"limitations":[30],"traditional":[32],"geometric":[33],"methods,":[34],"this":[35],"implements":[37],"SqueezeNet-based":[39],"Deep":[40],"Convolutional":[41],"Neural":[42],"Network":[43],"(DCNN)":[44],"rapid":[46],"eye-state":[47],"classification.":[48],"Comparative":[49],"analysis":[50],"with":[51,93],"various":[52],"pretrained":[53],"DCNN":[54],"models":[55],"indicates":[56],"that":[57],"SqueezeNet":[58],"provides":[59],"an":[60],"optimal":[61],"balance":[62],"accuracy":[64,170],"and":[65,72,97,110,119,154,171],"efficiency,":[66,174],"requiring":[67],"only":[68],"1.24":[69],"million":[70],"parameters":[71],"minimal":[74],"memory":[75],"footprint":[76],"5.2":[78],"MB.":[79],"For":[80],"contour":[82,128],"demarcation,":[83],"proposed":[85,136],"algorithm":[86,137],"combines":[87],"Circular":[89],"Hough":[90],"Transform":[91],"(CHT)":[92],"global":[94],"gray-level":[95],"statistics":[96],"anatomical":[98],"constraints":[99],"to":[100],"facilitate":[101],"reliable":[102],"localization.":[104],"Utilizing":[105],"image":[106],"decimation,":[107],"percentile-based":[108],"thresholding,":[109],"Canny":[111],"edge":[112],"detection,":[113],"it":[114],"systematically":[115],"delineates":[116],"limbic":[118],"pupillary":[120],"boundaries.":[121],"improved":[123],"search":[124],"methodology":[125],"ensures":[126],"precise":[127],"delineation,":[129],"even":[130],"under":[131],"sub-optimal":[132],"imaging":[133],"circumstances.":[134],"The":[135],"was":[138],"validated":[139],"on":[140],"novel":[142],"dataset":[143],"encompassing":[144],"challenging":[145],"conditions":[146],"such":[147],"as":[148],"specular":[149],"reflections,":[150],"blur,":[151],"non-uniform":[152],"illumination,":[153],"varying":[155],"degrees":[156],"occlusion,":[158],"including":[159],"Experimental":[165],"results":[166],"demonstrate":[167],"superior":[168],"significant":[172],"computational":[173],"underscoring":[175],"model\u2019s":[177],"potential":[178],"real-time":[180],"applications":[182],"unconstrained":[184],"environments.":[185]},"counts_by_year":[],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2026-04-18T00:00:00"}
