Title:
A Simple Shape Prior Model for Iris Image Segmentation
A Simple Shape Prior Model for Iris Image Segmentation
| dc.contributor.author | Bishop, Daniel A. | |
| dc.contributor.author | Yezzi, Anthony, Jr. | |
| dc.contributor.corporatename | Georgia Institute of Technology. Laboratory of Computational Computer Vision | en_US |
| dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
| dc.date.accessioned | 2015-01-27T13:40:02Z | |
| dc.date.available | 2015-01-27T13:40:02Z | |
| dc.date.issued | 2011 | |
| dc.description | ©2011 SPIE - Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. | en_US |
| dc.description | Presented at Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring; and Biometric Technology for Human Identification VIII, April 25, 2011, Orlando, Florida. | |
| dc.description | http://dx.doi.org/10.1117/12.883911 | |
| dc.description.abstract | In order to make biometric systems faster and more user-friendly, lower-quality images must be accepted. A major hurdle in this task is accurate segmentation of the boundaries of the iris in these images. Quite commonly, circle-fitting is used to approximate the boundaries of the inner (pupil) and outer (limbic) boundaries of the iris, but this assumption does not hold for off-axis or otherwise non-circular boundaries. In this paper we present a novel, foundational method for elliptical segmentation of off-axis iris images. This method uses active contours with constrained flow to achieve a simplified form of shape prior active contours. This is done by calculating a region-based contour evolution and projecting it upon a properly chosen set of vectors to confine it to a class of shapes. In this case, that class of shapes is ellipses. This serves to regularize the contour, simplifying the curve evolution and preventing the development of irregularities that present challenges in iris segmentation. The proposed method is tested using images from the UBIRIS v.1 and CASIA-IrisV3 image data sets, with both near-ideal and off-axis images. Additional testing has been performed using the WVU Off Axis/Angle Iris Dataset, Release 1. By avoiding many of the assumptions commonly used in iris segmentation methods, the proposed method is able to accurately fit elliptical boundaries to off-axis images. | en_US |
| dc.embargo.terms | null | en_US |
| dc.identifier.citation | Daniel A. Bishop and Anthony Yezzi, "A simple shape prior model for iris image segmentation", Proc. SPIE 8029, Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring; and Biometric Technology for Human Identification VIII, 80291T (2011). | en_US |
| dc.identifier.doi | 10.1117/12.883911 | |
| dc.identifier.uri | http://hdl.handle.net/1853/53153 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Georgia Institute of Technology | en_US |
| dc.publisher.original | Society of Photo-Optical Instrumentation Engineers | |
| dc.subject | Active contours | en_US |
| dc.subject | Biometrics | en_US |
| dc.subject | Iris | en_US |
| dc.subject | Off-axis | en_US |
| dc.subject | Segmentation | en_US |
| dc.subject | Shape prior | en_US |
| dc.title | A Simple Shape Prior Model for Iris Image Segmentation | en_US |
| dc.type | Text | |
| dc.type.genre | Proceedings | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | School of Electrical and Computer Engineering | |
| local.contributor.corporatename | College of Engineering | |
| relation.isOrgUnitOfPublication | 5b7adef2-447c-4270-b9fc-846bd76f80f2 | |
| relation.isOrgUnitOfPublication | 7c022d60-21d5-497c-b552-95e489a06569 |