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| Year | Authors | Approach | Testing database | Accuracy results |
|
| 2002 |
Camus and Wildes [3] | Multiresolution coarse-to-fine strategy | Constrained iris images (640 without glasses, 30 with glasses) | Overall 98% (99.5% for subjects without glasses and 66.6% for subjects wearing glasses) |
|
| 2004 | Sung et al. [4] | Bisection method, canny edge-map detector, and histogram equalization | 3,176 images acquired through a CCD camera | 100% inner boundary and 94.5% for collarette boundary |
|
| 2004 | Bonney et al. [5] | Least significant bit plane and standard deviations | 108 images from CASIA v1 and 104 images from UNSA | Pupil detection 99.1% and limbic detection 66.5% |
|
| 2005 | Liu et al. [6] | Modification to Masek’s segmentation algorithm | 317 gallery and 4,249 probe images acquired using Iridian LG 2200 iris imaging system | 97.08% rank-1 recognition |
|
| 2006 |
Proença and Alexandre [7] | Moment functions dependent on fuzzy clustering | 1,214 good quality, 663 noisy images from 241 subjects in two sessions | 98.02% on good data set and 97.88% on noisy data set |
|
| 2008 | Pundlik et al. [8] | Markov random field and graph cut | WVU nonideal database | Pixel label error rate 5.9% |
|
| 2009 | He et al. [9] | Adaboost-cascade iris detector for iris center prediction | NIST Iris Challenge Evaluation (ICE) v 1.0, CASIA-Iris-V3-lamp, UBIRISv1.0 | 0.53% EER for ICEv1.0 and 0.75% EER for CASIA Iris-V3-lamp |
|
| 2010 |
Liu et al. [10] | -means cluster | CASIAv3 and UBIRISv2.0 | 1.9% false positive and 21.3% false negative (on a fresh data set not used to tune the system) |
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| 2010 | Tan et al. [11] | Gray distribution features and gray projection | CASIAv1 | 99.14% accuracy (processing time 0.484 s/image) |
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| 2011 | Bakshi et al. [12] | Image morphology and connected component analysis | CASIAv3 | 95.76% accuracy with processing (0.396 s/image) |
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