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Rotation Invariant Iris Recognition Method Adaptive to Ambient Lighting Variation Hironobu TAKANO Hiroki KOBAYASHI Kiyomi NAKAMURA Publication IEICE TRANSACTIONS on Information and Systems Vol.E90-D No.6 pp.955-962 Publication Date: 2007/06/01 Online ISSN: 1745-1361 DOI: 10.1093/ietisy/e90-d.6.955 Print ISSN: 0916-8532 Type of Manuscript: PAPER Category: Image Recognition, Computer Vision Keyword: iris recognition, rotation spreading neural network, rotation recognition, rotation correction, Full Text: PDF(793.8KB)>>
Summary: We previously proposed a rotation-spreading neural network (R-SAN net). This neural net can recognize the orientation of an object irrespective of its shape, and its shape irrespective of its orientation. The R-SAN net is suitable for orientation recognition of a concentric circular pattern such as an iris image. Previously, variations of ambient lighting conditions affected iris detection. In this study, we introduce brightness normalization for accuracy improvement of iris detection in various lighting conditions. Brightness normalization provides high accuracy iris extraction in severe lighting conditions. A recognition experiment investigated the characteristics of rotation and shape recognition for both learned and un-learned iris images in various plane rotations. The R-SAN net recognized the rotation angle for the learned iris images in arbitrary orientation, but not for un-learned iris images. Thus, the variation of the rotation angle was corrected only for learned irises, but not un-learned irises. Although the R-SAN net rightly recognized the learned irises, it could not completely reject the un-learned irises as unregistered irises. Using the specific orientation recognition characteristics of the R-SAN net, a minimum distance was introduced as a new shape recognition criterion for the R-SAN net. In consequence, the R-SAN net combined with the minimum distance rightly recognized both learned (registered) and un-learned irises; the unregistered irises were correctly rejected. | ||||||||||
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