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Reference TypeConference Paper (Conference Proceedings)
Last Update2005: (UTC) administrator
Metadata Last Update2020: (UTC) administrator
Citation KeyMorimotoSantMuni:2005:AuIrSe
TitleAutomatic iris segmentation using active near infra red lighting
Access Date2021, Dec. 07
Number of Files1
Size568 KiB
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Author1 Morimoto, Carlos Hitoshi
2 Santos, Thiago Teixeira
3 Muniz, Adriano Saturno
Affiliation1 Department of Computer Science of the Institute of Mathmatics and Statistics of the University of São Paulo
EditorRodrigues, Maria Andréia Formico
Frery, Alejandro César
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)
Conference LocationNatal
Date9-12 Oct. 2005
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2008-07-17 14:11:01 :: hitoshi -> banon ::
2008-08-26 15:17:03 :: banon -> administrator ::
2009-08-13 20:37:59 :: administrator -> banon ::
2010-08-28 20:01:20 :: banon -> administrator ::
2020-02-19 03:19:23 :: administrator -> :: 2005
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Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
Keywordsiris segmentation
pupil detection
near infra red lighting
AbstractThis paper introduces a fast, robust and accurate iris segmentation technique based on active lighting. The geometry of the light sources, a single camera and the eye facilitates the detection of the pupil and the automatic selection of the most appropriate image for biometric identification from the video stream, minimizing the effects of noise, distortion and occlusion during the image acquisition process. Two near infrared (NIR) light sources (that are invisible to the human eye) are synchronized with the video signal. One of the light sources is placed near the optical axis of the camera, and generates a bright pupil image. The second light is placed off-axis, generating dark pupil images. These two images can be easily combined to segment the pupil region, and the corneal reflection of the light sources can be used to select best quality images. The pupil position is then used to segment the iris and eyelids using a coarse-to-fine strategy. Experimental results with a real-time prototype show the quality of the iris segmentation.
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