Iris segmentation is the process of defining the valid part of the eye image used for further processing (feature extraction, matching and decision making). Segmentation of the iris mostly starts with pupil boundary segmentation. Most pupil segmentation techniques are based on the assumption that the pupil is circular shape. In this paper, we propose a new pupil segmentation technique which combines shape, location and spatial information for accurate and efficient segmentation of the pupil. Initially, the pupil’s position and radius is estimated using a statistical approach and circular Hough transform. In order to segment the irregular boundary of the pupil, an active contour model is initialized close to the estimated boundary using information from the first step and segmentation is achieved using energy minimization based active contour. Pre-processing and post-processing were carried out to remove noise and occlusions respectively. Experimental results on CASIA V1.0 and 4.0 shows that the proposed method is highly effective at segmenting irregular boundaries of the pupil.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.