Optical approach for iris segmentation and tracking

In this paper, an autonomous active contour model based on the optical correlation algorithm is proposed. Optical correlation is used to calculate iris and pupil areas with a digital simulation of the Vander Lugt correlator. This area term computation assists the model to define an initial contour and at a later stage, to calculate terms in the energy expression. In the proposed model, several reference images called filters of iris and pupil have been introduced. Applied to three iris database and iris motion video, the proposed model enables us to reach better segmentation and tracking accuracy performance of irises.

[1]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[2]  James R. Cooper,et al.  Locating the Iris: A First Step to Registration and Identification , 2003, SIP.

[3]  B. V. K. Vijaya Kumar,et al.  Iris Verification Using Correlation Filters , 2003, AVBPA.

[4]  Sridha Sridharan,et al.  Fusing shrinking and expanding active contour models for robust iris segementation , 2010, 10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010).

[5]  Laurent D. Cohen,et al.  On active contour models and balloons , 1991, CVGIP Image Underst..

[6]  Robyn A. Owens,et al.  Location of the pupil-iris border in slit-lamp images of the cornea , 1999, Proceedings 10th International Conference on Image Analysis and Processing.

[7]  L. Cohen NOTE On Active Contour Models and Balloons , 1991 .

[8]  Rui Chen,et al.  Iris segmentation for non-cooperative recognition systems , 2011 .

[9]  Junaed Sattar Snakes , Shapes and Gradient Vector Flow , 2022 .

[10]  B. V. K. Vijaya Kumar,et al.  Application of Correlation Filters for Iris Recognition , 2013, Handbook of Iris Recognition.

[11]  A. B. Vander Lugt,et al.  Signal detection by complex spatial filtering , 1964, IEEE Trans. Inf. Theory.

[12]  Yihong Gong,et al.  Active contour model based on local and global intensity information for medical image segmentation , 2016, Neurocomputing.

[13]  Libor Masek,et al.  MATLAB Source Code for a Biometric Identification System Based on Iris Patterns , 2003 .

[14]  Mohammed Bennamoun,et al.  Iris recognition using class-specific dictionaries , 2017, Comput. Electr. Eng..

[15]  Madasu Hanmandlu,et al.  IRIS based authentication using local principal independent components , 2016 .

[16]  John Daugman,et al.  New Methods in Iris Recognition , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[17]  John Daugman,et al.  Probing the Uniqueness and Randomness of IrisCodes: Results From 200 Billion Iris Pair Comparisons , 2006, Proceedings of the IEEE.

[18]  John Daugman,et al.  High Confidence Visual Recognition of Persons by a Test of Statistical Independence , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[20]  Guy Perkins,et al.  A validated active contour method driven by parabolic arc model for detection and segmentation of mitochondria. , 2016, Journal of structural biology.

[21]  Chunming Li,et al.  Active contours driven by local Gaussian distribution fitting energy , 2009, Signal Process..

[22]  Sotirios A. Tsaftaris,et al.  Image-based plant phenotyping with incremental learning and active contours , 2014, Ecol. Informatics.

[23]  Hamid R. Tizhoosh,et al.  IRIS Segmentation: Detecting Pupil, Limbus and Eyelids , 2006, 2006 International Conference on Image Processing.

[24]  Michele Nappi,et al.  WIRE: Watershed based iris recognition , 2016, Pattern Recognit..

[25]  Chunming Li,et al.  Minimization of Region-Scalable Fitting Energy for Image Segmentation , 2008, IEEE Transactions on Image Processing.

[26]  Pheng-Ann Heng,et al.  Parametric active contours for object tracking based on matching degree image of object contour points , 2008, Pattern Recognit. Lett..

[27]  Xiaobo Zhang,et al.  Texture removal for adaptive level set based iris segmentation , 2010, 2010 IEEE International Conference on Image Processing.

[28]  Xuelong Li,et al.  Global structure constrained local shape prior estimation for medical image segmentation , 2013, Comput. Vis. Image Underst..

[29]  Claire Chalopin,et al.  Active contours driven by Cuckoo Search strategy for brain tumour images segmentation , 2016, Expert Syst. Appl..

[30]  John Daugman,et al.  How iris recognition works , 2002, IEEE Transactions on Circuits and Systems for Video Technology.

[31]  Marios Savvides,et al.  Correlation Pattern Recognition for Face Recognition , 2006, Proceedings of the IEEE.

[32]  B. V. K. Vijaya Kumar,et al.  Correlation Pattern Recognition , 2002 .

[33]  Arun Ross,et al.  Iris Segmentation Using Geodesic Active Contours , 2009, IEEE Transactions on Information Forensics and Security.

[34]  Lei Zhang,et al.  Active contours driven by local image fitting energy , 2010, Pattern Recognit..

[35]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.