A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Some Defects in Finite-Difference Edge Finders
IEEE Transactions on Pattern Analysis and Machine Intelligence
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Personal Identification Based on Iris Texture Analysis
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
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
Indexing Multimodal Biometric Databases Using Kd-Tree with Feature Level Fusion
ICISS '08 Proceedings of the 4th International Conference on Information Systems Security
An efficient technique for indexing multimodal biometric databases
International Journal of Biometrics
Biometric Based Unique Key Generation for Authentic Audio Watermarking
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
On a methodology for robust segmentation of nonideal iris images
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
A gaze tracking method as an IPTV interface
ICACT'10 Proceedings of the 12th international conference on Advanced communication technology
Edge curvature and convexity based ellipse detection method
Pattern Recognition
Statistical texture analysis-based approach for fake iris detection using support vector machines
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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In this paper, a new iris segmentation method for Hand-held capture device is proposed. First, the pupil is binarized using the intensity threshold, then use morphologic method to denoise the eyelashes and eyelids noise. The geometrical method is used to calculate the coordinates of the pupil. Second, the outer (or limbus) boundary is localized using the shrunk image with the Hough transform and modified Canny edge detector in order to reduce computational cost. Third, the eyelids which are constrained to be within the outer boundary are estimated using the polynomial fitting method. The segmentation method was implemented and tested on iris database set which is captured by hand-held optical sensor device. Experimental results show that the proposed algorithm can separate the iris from the surrounding noises with good speed and accuracy.