DocumentCode :
2422191
Title :
Iris boundaries segmentation using the generalized structure tensor. A study on the effects of image degradation
Author :
Alonso-Fernandez, Fernando ; Bigun, Josef
Author_Institution :
Halmstad Univ., Halmstad, Sweden
fYear :
2012
fDate :
23-27 Sept. 2012
Firstpage :
426
Lastpage :
431
Abstract :
We present a new iris segmentation algorithm based on the Generalized Structure Tensor (GST), which also includes an eyelid detection step. It is compared with traditional segmentation systems based on Hough transform and integro-differential operators. Results are given using the CASIA-IrisV3-Interval database. Segmentation performance under different degrees of image defocus and motion blur is also evaluated. Reported results shows the effectiveness of the proposed algorithm, with similar performance than the others in pupil detection, and clearly better performance for sclera detection for all levels of degradation. Verification results using 1D Log-Gabor wavelets are also given, showing the benefits of the eyelids removal step. These results point out the validity of the GST as an alternative to other iris segmentation systems.
Keywords :
Gabor filters; Hough transforms; eye; image motion analysis; image segmentation; integro-differential equations; iris recognition; object detection; tensors; wavelet transforms; 1D log-Gabor wavelet; CASIA-IrisV3-Interval database; GST; Hough transform; eyelid detection; eyelid removal; generalized structure tensor; image defocus; image degradation; integro-differential operator; iris boundaries segmentation; iris segmentation algorithm; motion blur; pupil detection; sclera detection; segmentation performance; Accuracy; Eyelids; Image edge detection; Image segmentation; Iris recognition; Motion segmentation; Tensile stress;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biometrics: Theory, Applications and Systems (BTAS), 2012 IEEE Fifth International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
978-1-4673-1384-1
Electronic_ISBN :
978-1-4673-1383-4
Type :
conf
DOI :
10.1109/BTAS.2012.6374610
Filename :
6374610
Link To Document :
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