Biometric verification of a subject through eye movements
Matching digital fingerprint, face or iris images, biometric verification of persons has advanced. Notwithstanding the progress, this is no easy computational task because of great numbers of complicated data. Since the 1990s, eye movements previously only applied to various tests of medicine and ps...
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| Published in | Computers in biology and medicine Vol. 43; no. 1; pp. 42 - 50 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Elsevier Ltd
01.01.2013
Elsevier Limited |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Matching digital fingerprint, face or iris images, biometric verification of persons has advanced. Notwithstanding the progress, this is no easy computational task because of great numbers of complicated data. Since the 1990s, eye movements previously only applied to various tests of medicine and psychology are also studied for the purpose of computer interfaces. Such a short one-dimensional measurement signal contains less data than images and may therefore be simpler and faster to recognize. Using saccadic eye movements we developed a computational verification method to reliably distinguish a legitimate person or a subject in general from others. We tested features extracted from signals recorded from saccade eye movements. We used saccades of 19 healthy subjects and 21 otoneurological patients recorded with electro-oculography and additional 40 healthy subjects recorded with a videocamera system. Verification tests produced high accuracies. |
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| AbstractList | Matching digital fingerprint, face or iris images, biometric verification of persons has advanced. Notwithstanding the progress, this is no easy computational task because of great numbers of complicated data. Since the 1990s, eye movements previously only applied to various tests of medicine and psychology are also studied for the purpose of computer interfaces. Such a short one-dimensional measurement signal contains less data than images and may therefore be simpler and faster to recognize. Using saccadic eye movements we developed a computational verification method to reliably distinguish a legitimate person or a subject in general from others. We tested features extracted from signals recorded from saccade eye movements. We used saccades of 19 healthy subjects and 21 otoneurological patients recorded with electro-oculography and additional 40 healthy subjects recorded with a videocamera system. Verification tests produced high accuracies. Matching digital fingerprint, face or iris images, biometric verification of persons has advanced. Notwithstanding the progress, this is no easy computational task because of great numbers of complicated data. Since the 1990s, eye movements previously only applied to various tests of medicine and psychology are also studied for the purpose of computer interfaces. Such a short one-dimensional measurement signal contains less data than images and may therefore be simpler and faster to recognize. Using saccadic eye movements we developed a computational verification method to reliably distinguish a legitimate person or a subject in general from others. We tested features extracted from signals recorded from saccade eye movements. We used saccades of 19 healthy subjects and 21 otoneurological patients recorded with electro-oculography and additional 40 healthy subjects recorded with a videocamera system. Verification tests produced high accuracies.Matching digital fingerprint, face or iris images, biometric verification of persons has advanced. Notwithstanding the progress, this is no easy computational task because of great numbers of complicated data. Since the 1990s, eye movements previously only applied to various tests of medicine and psychology are also studied for the purpose of computer interfaces. Such a short one-dimensional measurement signal contains less data than images and may therefore be simpler and faster to recognize. Using saccadic eye movements we developed a computational verification method to reliably distinguish a legitimate person or a subject in general from others. We tested features extracted from signals recorded from saccade eye movements. We used saccades of 19 healthy subjects and 21 otoneurological patients recorded with electro-oculography and additional 40 healthy subjects recorded with a videocamera system. Verification tests produced high accuracies. Abstract Matching digital fingerprint, face or iris images, biometric verification of persons has advanced. Notwithstanding the progress, this is no easy computational task because of great numbers of complicated data. Since the 1990s, eye movements previously only applied to various tests of medicine and psychology are also studied for the purpose of computer interfaces. Such a short one-dimensional measurement signal contains less data than images and may therefore be simpler and faster to recognize. Using saccadic eye movements we developed a computational verification method to reliably distinguish a legitimate person or a subject in general from others. We tested features extracted from signals recorded from saccade eye movements. We used saccades of 19 healthy subjects and 21 otoneurological patients recorded with electro-oculography and additional 40 healthy subjects recorded with a videocamera system. Verification tests produced high accuracies. |
| Author | Zhang, Youming Rasku, Jyrki Juhola, Martti |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23177205$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_17759_exppsy_2020130405 crossref_primary_10_1109_TBIOM_2021_3130798 crossref_primary_10_1016_j_visres_2017_03_001 crossref_primary_10_3390_biomimetics8040378 crossref_primary_10_1016_j_procs_2020_09_144 crossref_primary_10_3390_s16020227 crossref_primary_10_1109_JBHI_2016_2551862 crossref_primary_10_1371_journal_pone_0196125 crossref_primary_10_1016_j_compag_2016_03_014 crossref_primary_10_1142_S0218001414560151 crossref_primary_10_1145_3161410 crossref_primary_10_1016_j_patrec_2015_07_034 crossref_primary_10_1109_LSP_2014_2374338 crossref_primary_10_1109_TIFS_2018_2850032 crossref_primary_10_1016_j_patrec_2016_11_002 crossref_primary_10_1049_iet_bmt_2014_0044 crossref_primary_10_1016_j_imavis_2020_103980 crossref_primary_10_1016_j_patrec_2015_06_019 crossref_primary_10_1089_neu_2018_5673 |
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| Keywords | Saccades Biometric user verification Eye movements Classification Machine learning |
| Language | English |
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| Snippet | Matching digital fingerprint, face or iris images, biometric verification of persons has advanced. Notwithstanding the progress, this is no easy computational... Abstract Matching digital fingerprint, face or iris images, biometric verification of persons has advanced. Notwithstanding the progress, this is no easy... |
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| SubjectTerms | Adult Aging Behavior Biometric Identification - methods Biometric user verification Biometrics Cellular telephones Classification Eye movements eyes face Female Hospitals Humans Internal Medicine Machine learning Male medicine Middle Aged Other Otolaryngology patients people Photic Stimulation psychology Saccades Saccades - physiology Signal Processing, Computer-Assisted Studies vision |
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| Title | Biometric verification of a subject through eye movements |
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