Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
On active contour models and balloons
CVGIP: Image Understanding
Crystal growth and dendritic solidification
Journal of Computational Physics
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Iris Segmentation Method for Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Iris Feature Extraction Using 2D Phase Congruency
ICITA '05 Proceedings of the Third International Conference on Information Technology and Applications (ICITA'05) Volume 2 - Volume 02
Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
Toward Accurate and Fast Iris Segmentation for Iris Biometrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris feature extraction using independent component analysis
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
UBIRIS: a noisy iris image database
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Robust iris recognition using advanced correlation techniques
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
New Methods in Iris Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
Exploring multispectral Iris recognition beyond 900nm
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Exploiting the "Doddington Zoo" effect in biometric fusion
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Iris segmentation in non-ideal images using graph cuts
Image and Vision Computing
Engineering Applications of Artificial Intelligence
Fast and iterative algorithm for iris detection with orthogonal polynomials transform
Proceedings of the 2011 International Conference on Communication, Computing & Security
Unideal iris segmentation using region-based active contour model
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
Speed-up multi-stage non-cooperative iris recognition
International Journal of Biometrics
Sensitivity analysis for biometric systems: A methodology based on orthogonal experiment designs
Computer Vision and Image Understanding
Effective elliptic fitting for iris normalization
Computer Vision and Image Understanding
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The richness and apparent stability of the iris texture make it a robust biometric trait for personal authentication. The performance of an automated iris recognition system is affected by the accuracy of the segmentation process used to localize the iris structure. Most segmentation models in the literature assume that the pupillary, limbic, and eyelid boundaries are circular or elliptical in shape. Hence, they focus on determining model parameters that best fit these hypotheses. However, it is difficult to segment iris images acquired under nonideal conditions using such conic models. In this paper, we describe a novel iris segmentation scheme employing geodesic active contours (GACs) to extract the iris from the surrounding structures. Since active contours can 1) assume any shape and 2) segment multiple objects simultaneously, they mitigate some of the concerns associated with traditional iris segmentation models. The proposed scheme elicits the iris texture in an iterative fashion and is guided by both local and global properties of the image. The matching accuracy of an iris recognition system is observed to improve upon application of the proposed segmentation algorithm. Experimental results on the CASIA v3.0 and WVU nonideal iris databases indicate the efficacy of the proposed technique.