High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Location of the Pupil-Iris Border in Slit-Lamp Images of the Cornea
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Reliable and Fast Eye Finding in Close-up Images
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture detection for segmentation of iris images
SAICSIT '05 Proceedings of the 2005 annual research conference of the South African institute of computer scientists and information technologists on IT research in developing countries
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Effective Approach for Iris Recognition Using Phase-Based Image Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Toward Accurate and Fast Iris Segmentation for Iris Biometrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel iris segmentation using radial-suppression edge detection
Signal Processing
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
Edge detection in untextured and textured images-a common computational framework
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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
IEEE Transactions on Circuits and Systems for Video Technology
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A simple boundary extraction technique for irregular pupil boundary localization is proposed in this paper by designing a new Where-to-go approach that extracts the irregular pupil boundary points from the edge map. Initially, the input eye image is subjected to the orthogonal polynomials model and then Hartley's statistical hypothesis testing is employed to separate out the responses towards noise from those towards strong edges in the eye image. Then the proposed boundary extraction technique is employed to extract the pupil boundary points perfectly and it is independent of the specific eye image characteristics such as pupil deformation, poor contrast, poor brightness, etc. The proposed approach is adaptable to all monochrome databases and exhibits encouraging results when compared with the existing techniques.