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Active Contour without Edges vs GVF Active Contour for Accurate Pupil Segmentation

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 54 - Number 4
Year of Publication: 2012
Walid Aydi
Nouri Masmoudi
Lotfi Kamoun

Walid Aydi, Nouri Masmoudi and Lotfi Kamoun. Article: Active Contour without Edges vs GVF Active Contour for Accurate Pupil Segmentation. International Journal of Computer Applications 54(4):25-36, September 2012. Full text available. BibTeX

	author = {Walid Aydi and Nouri Masmoudi and Lotfi Kamoun},
	title = {Article: Active Contour without Edges vs GVF Active Contour for Accurate Pupil Segmentation},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {54},
	number = {4},
	pages = {25-36},
	month = {September},
	note = {Full text available}


Iris localization is a critical step for an iris recognition system because it directly affects the recognition rates. Consequently, in order to have reasonably accurate measures, we should estimate as many iris boundaries as possible which are defined by papillary and ciliary regions. Due to the contraction which is an intrinsic propriety of the pupil and the variations in the shooting angle, the pupil will not be a regular circle. So an active contour is suitable to accurately locate the iris boundaries. In this paper we focused on iris/pupil boundary and we proposed a new algorithm based on an active contour without edges applied in gray level image. First, we develop a new method to locate and fill the corneal reflection which is used not only to remove the highlight points that appear inside the pupil but also as an initial contour generator for the snake. Second, we propose to use the active contour without edges for precise pupil segmentation. This kind of snake can detect objects whose boundaries are not necessarily defined by gradient. Our algorithm seems to be robust to occlusion, specular reflection, variation in illumination and improves its efficiency in precision and time computation compared with AIPF and Gvf active contour. Another advantage is that the initial curve can be anywhere in the image and the contour will be automatically detected. The proposed algorithm is 2. 36 faster than GVF snake-based method for accurate pupil contour detection and integro-differential method with accuracy up to 99. 62% using CASIA iris database V3. 0 and up to 100% with CASIA iris database V1. 0.


  • H. -A. Park, K. R. Park, "Iris recognition based on score level fusion by using SVM", Pattern Recognition Letters, 28 (2007) 2019-2028.
  • Y. Adini, Y. Moses, and S. Ullman, "Face recognition: the problem of compensating for changes in illumination direction", IEEE Trans. Pattern Anal. Machine Intell. , 19 (1997) 721 - 732.
  • J. Daugman, "How Iris Recognition Works", IEEE Transactions on circuits and systems for video technology, 14 (2004) 21 - 30.
  • M. Nabti, A. Bouridane, "An effective and fast iris recognition system based on a combined multiscale", Pattern Recognition, 41 (2008) 868–879.
  • R. Wildes, Iris Recognition: "An Emerging Biometric Technology", Proceedings of the IEEE, 85 (1997) 1348 - 1363.
  • L. Masek, "Recognition of human iris patterns for biometric identification",The University of Western Australia, 2003.
  • S. Pundlik,D. Woodard, S. Birchfield, "Non-ideal iris segmentation using graph cuts", IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, (2008) 1 - 6.
  • J. Zuo, N. K. Ratha, J. H. Connell, "A new approach for iris segmentation", IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, (2008) 1-6.
  • J. Daugman, "New Methods in Iris Recognition", IEEE Transactions on systems, man, and cybernetics, 37 (2007)1167-1175.
  • Z. He, T. Tan, Z. Sun, and X. Qiu, "Toward accurate and fast iris segmentation for iris biometrics", IEEE Transactions on Pattern analysis and machine intelligence, 31 (2009) 1670 - 1684.
  • K. Nguyen, C. Fookes, and S. Sridharan, "Fusing shrinking and expanding active contour models for robust iris segmentation", 10th International Conference on Information Science, Signal Processing and their Applications, (2010) 185 - 188.
  • A. jarjes, K. Wang and G. J . Mohammed, "GVF snake-based method for accurate pupil contour detection", Information technology Journal, 9 (2010) 1653-1658.
  • C. Bastos, I. Tsang and G. Calvalcanti, "A combined pulling & pushing and active contour method for pupil segmentation", ICASSP (2010).
  • Z. Zhou and X. Geng, "Projection Functions for Eye Detection", Pattern Recognition, 37 (2004) 1049-1056.
  • C. Xu and J. L. Prince, "Snakes, shapes, and gradient vector flow", IEEE Transactions on image processing, 7 (1998) 359 - 369.
  • A. Ebrahim Yahya, M. Jan Nordin, "A New Technique for Iris Localization", International Scientific Conference Computer Science, (2008).
  • http://www. shawnlankton. com/2007/05/active-contours/, T. F. chan, L. A. Vese , "Active Contours Without Edges", IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 10, NO. 2, FEBRUARY 2001.
  • http://en. wikipedia. org/wiki/Level_set_method, D. H. Perez, "level set method applied to topology optimization", grupo de optimizacion structural (GOE), February 2012.
  • R. Whitaker, "A Level-Set Approach to 3D Reconstruction from Range Data", the International Journal of Computer Vision, 29 (1998) 203-231.
  • C. Phillips, "The Level-Set Method", MIT Undergraduate Journal of Mathematics, (1999).
  • http://en. wikipedia. org/wiki/Courant%E2%80%93Friedrichs%E2%80%93Lewy_condition, R. Courant, K. O. Friedrichs, H. Lewy, "Ueber die partiellen Differenzgleichungen der mathematische Physik" Math Ann. , 100 (1928) pp. 32–74.
  • M. Sussman, P. Smereka and S. Osher, "A level set approach for computing solutions to incompressible two-phase flow", University of California, Los Angeles, 14 (1994) 146-159.
  • S. Lankton, "Sparse Field Methods", Technical Report, 2009.
  • W. Aydi, N. Masmoudi, L. Kamoun, "New corneal reflection removal method used in iris recognition system", World Academy of Science, Engineering and Technology 77 (2011).
  • J. Huang, X. You, Y. Yan Tang a, b, L. Du, Y. Yuan, "A novel iris segmentation using radial-suppression edge detection", Journal signal processing,89 (2009) 2630-2643.
  • Image understanding for iris biometrics: "A survey Kevin W. Bowyer ", Karen Hollingsworth, Patrick J. Flynn