Human Iris Recognition in Unconstrained Environments by ijcsiseditor1


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									                                                                (IJCSIS) International Journal of Computer Science and Information Security,
                                                                                                                     Vol. 9, No. 7, July 2011

               Human Iris Recognition In Unconstrained
               Mohammad Ali Azimi Kashani                                               Mohammad Reza Ramezanpoor Fini
    Department of Computer Science & Research Branch                            Department of Computer Science & Research Branch
        Islamic Azad University Branch Shoushtar                                    Islamic Azad University Branch Shoushtar
                     Shoushtar, Iran                                                             Shoushtar, Iran

                                                           Mahdi Mollaei Arani
                                          Department of Computer Science & Research Branch
                                                       Payame Noor University
                                                           Ardestan, Iran

Abstract—Designation of iris is one of biometric recognition
methods .That use modal recognition technique and is base on                           II.     AVAILABLE IRIS RECOGNITION SYSTEM
pictures whit high equality of eye iris .Iris modals in comparison             Daugman technique [3, 9] is one of oldest iris recognition
whit other properties in biometrics system are more resistance             system. These systems include all of iris recognition process:
and credit .In this paper we use from fractals technique for iris          Taking picture, assembling, coding tissue and adaption.
recognition. Fractals are important in these aspects that can
express complicated pictures with applying several simple codes.
Until, That cause to iris tissue change from depart coordination           A. Daugman techniques
to polar coordination and adjust for light rates. While                        Daugman algorithm [3,9] is the famous iris algorithm. In
performing other pre-process, fault rates will be less than EER,           this algorithm, iris medaling by two circles than aren’t
and lead to decreasing recognition time, account table cost and            necessary certified. every circle defined whit there parameters
grouping precise improvement.                                              ( xo , y o , r ) that ( x o , y o ) are center of circle with r radios .
                                                                           Use - a differential – integral performer for estimating 3
     Keywords-Biometrics; Identitydistinction;Identity erification;        parameter in every circle bound. All pictures search rather to
Iris modals.                                                               increasing r radius to maximize following Equation (1):

                       I.     INTRODUCTION                                                                                I ( x, y )
                                                                                             G (r ) *                                ds
    Biometric use for identity distinction of input sample                                              r   x0 , y0 , r     2 r
compare to one modal and in some case use for recognition                       In this formulate ( x , y ) is picture light intensify , ds is
special people by determined properties .Using password or                 curve circle , 2 r use for normalization in tetras G( r ) is Gus
identity card. Can create some problems like losing forgetting             filter as used for flotation , and * is convolution performed
thief. So using from biometric property for reason of special              (agent).
property will be effective. Biometric parameters dived to group
base on figure one [1]: Physiologic: this parameter is related to
fig.1 of body human. Behavioral: this parameter is related to                               III. SUGGESTIVE ALGORITHM
behavior of one person.                                                        In this algorithm, we use from new method for identity
                                                                           distinction base on fractal techniques, specially used fractal
                                                                           codes as coding iris tissue modal. For testing suggestive
                                                                           method, we used from available pictures in picture base of bath
                                                                           university. General steps of iris distinction would be as follow.
                                                                           Clearly indicate advantages, limitations and possible

             Figure 1. grouping some biometrics property
                                                                             Figure 2. Sample of available pictures in iris database of Bath University

                                                                                                               ISSN 1947-5500
                                                                   (IJCSIS) International Journal of Computer Science and Information Security,
                                                                                                                        Vol. 9, No. 7, July 2011
A. Iris assembling                                                             Then separated iris tissue control for light intensifies.
    The main goal of this part is recognition of iris area in eye           Means picture contrast increased to iris tissue recognize very
pictures. For this reason, we should recognize internal and                 good. In Fig.6 you can see sample of norm led iris tissue.
external bound in iris by two circles. One method for
assembling is using from fractal dimension. In Fig.3 we present
dimension of Hough circle and in Fig. 4 show the Iris
normalization, is more than 1 threshold. For accounting of
fractal diminution, the picture dived to Blocks with 40 pixel
width. As showed in picture, pupil and eye- lid areas
recognized very good.                                                                       Figure 6. Diagram of normal iris picture.

                                                                            C. Iris tissue coding
                                                                                 In this step, we should coding iris tissue pixels set, and use
                                                                            it for comparing between 2 iris pictures. In suggestive methods.
                                                                            We use from fractal code. So fractal code of normal iris
                                                                            account. And this code as one modal saves in data base. To
                                                                            used for recognition and comparing iris pictures. In next step,
                                                                            we should encoding input picture with this fractal codes. So I
                                                                            need to change all pictures to standard size. For accounting
                                                                            fractal code first normal iris picture change to one rectangle
                                                                            64*180 pixels. So fractal codes for different iris have same
                     Figure 3.   output hough circle

                                                                                    Figure 7. Normal iris picture in diminution 64*180 pixels

                                                                            D. Change range to wide blocks
                                                                                Main step in accounting fractal picture coding is changing
                                                                            range to wide blocks. For every wide block copy of range
                      Figure 4. Iris normalization                          block compare to that block. W changing is combination of
                                                                            geometrics and light changing. In case of I grey picture, if z
B. Iris normalization                                                       express pixel light intensify in (x, y), we can show w as matrix
                                                                            as follow:
    In this step, should decant coordination change to polar
coordination. For this reason , 128 perfect circle next to pupil
center and with starting from pupil radius toward out , separate                                 x      a    b    0 x      e
from iris , pour pixels on these circles in one rectangle , in this                         W    y      c    d    0 y      f
way iris that was the form of circle trope , change to rectangle,                                z      0    0    s z      o
it means iris from Decoct coordination change to polar
coordination. In fig.5 you can watch iris polar coordination.                  f, a, b, c, d, e coefficient, control main aspect of changing
Since changing in light level, pupil environment of iris                    geometrical. While s, o recognized contrast and both of them
changed. We should control input light. However, it may                     recognize light parameters (fig.8). Changing geometrics
person interval different from camera, but size of iris doesn’t             parameters limit to hardness adaption. [11]
same in different pictures. So with choosing this 128 prefect
circles iris normalization done in respect to size.

          Figure 5. Diagram of polar coordination of iris tissue
                                                                                           Figure 8. Picture of rang and wide blocks

                                                                                                            ISSN 1947-5500
                                                                                                      (IJCSIS) International Journal of Computer Science and Information Security,
                                                                                                                                                           Vol. 9, No. 7, July 2011
    Comparing range wide in a 3 steps process. One of base
eight directions applied on selected range block. Then, oriented
                                                                                                                             D ( x‚y)   max
                                                                                                                                          0 i N
                                                                                                                                                   xi   yi

range block, become minimum till be equal to wide block Rk.
If we want general changed be contradictor, wide should be
range block [11]. However, present ting picture as set of                                                      F. Suggestive method simulation
changed blocks, don't present precise copy, but it´s good                                                          Suggestive method for identity recognition performed on
approximate. Minimizing fault between Rk and w (Dj) can                                                        subset iris picture data base in Bath University. Available
minimize fault between estimated and main picture. If ri and d                                                 subset include 1000 picture from 25 different persons. 20
and I=1‚…‚n be pixel amounts relate to blocks having same                                                      pictures from left eye and 20 picture form right eye were
size Rk and shrink , fault and ERR is as following[11] :                                                       showed. Since iris left and right eye is different in every
                                                                                                               person. Among every 50 eyes, from 20 pictures, 6 pictures are
                            n                                                                                  considered for teaching and testing (fig.9.10.11).
                Err                     ( s .d i       o       ri ) 2
                           i 1

              Err n.o 2                  (s 2.d i2 2.s.d i.o 2.s.d i.ri 2.o.ri ri2)
                                i 1

                                    ( 2.s.di2              2.di. .o           2.di .r )
                                                                                    i     0
                 s         i 1
                                                   n                    n
                Err        2.n.o                       ( 2.n.o                 ( 2.s.di   2.r )
                                                                                            i     0
                                              i 1                       i 1

   It happens when [10]:
                           n                                   n                n
                  n           d .r                                d                r
                           i 1 i i                             i 1 i            i 1 i
                                    n                              n
                       n                    di 2           (          d        )2
                                    i 1                            i 1 i

                1           n                              n
          o                         ri         s              d
                n           i                              i 1 i

    One of advantage of suggestive method for iris recognition
                                                                                                                  Figure 9. curve ROC relate to suggestive identity verification system.
is that when registering person, we save input fractal code of
person iris picture as modal in data base, and so with regard to
compressing property of fractal codes, we have less weight data

E. Grouping and adapting
    In this respect we should compare input picture with
available modals in data base system, and achieve similarity
between them. For this reason, iris norm led picture encoding
with available fractal codes in data base. For recognition
similarity between input and encoding picture, used form
interval between them. Nominal similarity size is 0 and 1 [10].
Interval form mincosci defined base on soft LP:

                                    N 1
               d p (x‚y)        p           (xi yi ) p
                                    i 0

                                                                                                                Figure 10. curve ROC RELATES to suggestive identity verification system
   When p             , achieved L :                                                                                        with regard to adoptions numbers. (n= 1, 2, 3, 4, 5)

                                                                                                                                               ISSN 1947-5500
                                                                         (IJCSIS) International Journal of Computer Science and Information Security,
                                                                                                                              Vol. 9, No. 7, July 2011
                                                                                    and sub fractal techniques. Also for more precise identity
                                                                                    distinction and adaptation use more various grouping
                                                                                    techniques like k (nearest neighborhood).

                                                                                    [1]    A. K. Jain, R. Bole, S. Penchant, “Biometrics: Personal Identification in
                                                                                           Network Society.” Kluwer Academic Publishers, 1999.
                                                                                    [2]    A. K. Jain, A. Ross and S. Pankanti, "Biometrics: A Tool for
                                                                                           Information Security" IEEE Transactions on Information Forensics and
                                                                                           Security 1st (2), 2006.
                                                                                    [3]    International Biometric Group, Independent Testing of Iris Recognition
                                                                                           Technology, May 2005.
                                                                                    [4]    J. Daugman, “How iris recognition works”, IEEE Trans. Circuits
                                                                                           Systems Video Technol. v14i1. 21-30, 2004.
                                                                                    [5]    J. Daugman, “High confidence visual recognition of persons by a test of
                                                                                           statistical independence”, IEEE Transactions on Pattern Analysis and
                                                                                           Machine Intelligence, vol. 15, pp.1148-1161, 1993.
 Figure 11. curve ROC relate to suggestive identity verification system with        [6]    J. Daugman, “The importance of being random: Statistical principles of
                      regard to adoptions numbers.                                         iris recognition” Pattern Recognition 36, 279–291, 2003.
                                                                                    [7]    J.Daugman,       “New      Methods      in    Iris    Recognition”.IEEE
                                                                                           TRANSACTIONS ON SYSTEMS, MAN, AND YBERNETICS, 2007.
                                                                                    [8]    J. Daugman, “Demodulation by complex-valued wavelets for stochastic
                   NUMBER . (N=1, 2, 3, 4, 5, 6)
                                                                                           pattern recognition” International Journal of Wavelets, Multiresolution
                                                                                           and Information Processing, 1(1):1–17, 2003.
       Identity Daugman         Identity suggestive        Picture                  [9]    J. Daugman, “New Methods in Iris Recognition”. IEEE
            method                    method             number(n)                         TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS,
       %96                     %88                       1 picture                         2007.
       %96                     %86                       2 picture                  [10]   H. Ebrahimpour-Komleh, Fractal Techniques for Face Recognition, PhD
       %96                     %94                       3 picture                         thesis, Queensland University of technology, 2004.
       %96                     %94                       4 picture                  [11]   H. Ebrahimpour-Komleh, V. Chandra., and S. Sridharan, "Face
                                                                                           recognition using fractal codes" Proceedings of International Conference
       %96                     %96                       5 picture                         on Image Processing(ICIP), vol. 3, pp. 58-61, 2009.
       %96                     %96.13                    6 picture                  [12]   H. Ebrahimpour-Komleh, V. Chandra, and S. Sridhar an, "Robustness to
                                                                                           expression variations in fractal-based face recognition" Sixth
                                                                                           International, Symposium on Signal Processing and its Applications,
                                                                                           vol. 1, pp. 359-362, 2001.
                           IV.    CONCLUSION
                                                                                    [13]   H. Ebrahimpour-Komleh, V. Chandra, and S. Sridhar an “An
    In this paper, we have proposed a new method base on                                   Application of Fractal Image-set Coding in Facial Recognition,”
fractal techniques for identity verification and recognition with                          Springer Verlag Lecture Notes in computer science, Volt 3072,
help of eye iris modals. For a lot of reasons that iris modals                             Biometric authentication, pp178-186, Springer-Velar, 2004.
have ran the than other biometrics properties it’s more
fantastic. In assembling part. It says that with using of light in                                             Mohammad A. Azimi Kashani              (Jun ’83)
tensely process techniques and modeling performance and                                                        received the B.S and M.S degrees in computer
Anny margin or can recognize iris internal bound. In                                                           engineering from Islamic Azad university of
normalization part centrifuged rules toward pupil center and                                                   Kashan and Dezfoul, Iran in 2006 and 2009
starting radius toward out, can determine noise originate from                                                 respectively. He works in the area of PCA and
eye-lash and eye-lid. Since in coding and encoding iris picture                                                his primary interest are in the theory of
                                                                                                               detection and estimation, including face
and we use fractal codes iris fractal codes save as modals in
                                                                                                               detection, eye detection, face and eye tracking.
data base. This method has same advantages like less weight of                                                 He accepted numerous papers on different
database .more security and relative good precise. when                             conferences for IEEE.
entering one person, iris picture encoding on fractal codes for
one step, to Euclid interval and interval minimum e method can
use .In suggestive system normalization part, iris tissue change                                             Mohammad R. Ramezanpour fini (sep’85)
form depart coordination to polar coordination and adjust light                                              received the B.S degree in computer
in tensely, while performing other preprocess, fault rate ERR                                                engineering from Islamic Azad university of
will be less than this amount .If used data base in iris                                                     Kashan , Iran, in 2007 and the M.S degree
distinction system be big, search time will be a lot. So, in                                                 from the Islamic Azad university of Arak,
grouping and adapting iris modals for reason of decreasing                                                   Iran, in 2010. His research interests are
distinction time, decreasing accounting cost and improving                                                   primarily in the fields of communication,
grouping precise, can use form diminution fractal. Also, it is                                               image processing and signal processing.
suggest using fractal codes as iris tissue property and using                                                Presently, he is working in image processing,
coding techniques fractal picture set for confine fractal codes                     cam-shift, particle filter and Kalman filter for estimate and tracking.

                                                                                                                       ISSN 1947-5500

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