20051739 Iris Recongition

8/9/2019 20051739 Iris Recongition

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1ABSTRACT

2 A biometric system provides automatic recognition of an individual based on some

sort of unique feature or characteristic possessed by the individual. Biometric systemshave been developed based on fingerprints, facial features, voice, hand geometry,

handwriting, the retina and the one presented in this thesis, the iris.

3 The objective of the project is to implement an opensource iris recognition system in

order to verify the claimed performance of the technology. The development tool used is

!AT"AB, and emphasis is on the software for performing recognition, and not hardware

for capturing an eye image.

#ris recognition analy$es the features that e%ist in the colored tissue

surrounding the pupil, which has 2&' points used for comparison, including rings,

furrows, and frec(les. #ris recognition uses a regular video camera system and can be

done from further away than a retinal scan. #t has the ability to create an accurate enough

measurement that can be used for #dentification purposes, not just verification.

The probability of finding two people with identical iris patterns is considered

to be appro%imately ) in )'&2*population of the earth is of the order )')'+. ot even one

egged twins or a future clone of a person will have the same iris patterns. The iris is

considered to be an internal organ because it is so well protected by the eyelid and the

cornea from environmental damage. #t is stable over time even though the person ages.

#ris recognition is the most precise and fastest of the biometric authentication methods.

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CHAPTER - 1

BIOMETRIC TECHNOLOGY

1.1 INTRODUCTION: A biometric system provides automatic recognition of an individual

based on some sort of unique feature or characteristic possessed by the individual.

Biometric systems have been developed based on fingerprints, facial features, voice, hand

geometry, handwriting, the retina and the one presented in this thesis, the iris.

Biometric systems wor( by first capturing a sample of the feature, such

as recording a digital sound signal for voice recognition, or ta(ing a digital colour image

for face recognition. The sample is then transformed using some sort of mathematical

function into a biometric template. The biometric template will provide a normalised,

efficient and highly discriminating representation of the feature, which can then be

objectively compared with other templates in order to determine identity. !ost biometric

systems allow two modes of operation. An enrolment mode for adding templates to a

database, and an identification mode, where a template is created for an individual and

then a match is searched for in the database of preenrolled templates.

A good biometric is characteri$ed by use of a feature that is0 highly

unique, stable and be easily captured and the chance of any two people having the same

characteristic will be minimal. Also the feature does not change over time .#n order to

provide convenience to the user, and prevent misrepresentation of the feature.

1.2 ADVANTAGES OF USING BIOMETRICS:

• /asier fraud detection

• Better than password1# or smart cards

• o need to memori$e passwords

• -equires physical presence of the person to be identified

• nique physical or behavioral characteristic

• annot be borrowed, stolen, or forgotten

• annot leave it at home

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1.3 TYPES OF BIOMETRICS:

4 hysical Biometrics

• 5inger print -ecognition

• 5acial -ecognition

• 6and 7eometry

• #-#8 -ecognition

• 9A

4Behavioral Biometrics

• 8pea(er -ecognition

• 8ignature

• :eystro(e

• ;al(ing style

1.4 IRIS RECOGNITION SYSTEM:

The purpose of


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#n the chapter 2, we will discuss about the #-#8 -ecognition system, its

strengths and wea(ness. #n the chapter 3, we will discuss about the implementation of

#-#8 recognition system. #n chapter >, we will discuss about the unwrapping technology

.#n chapter &, about the wavelet analysis. #n chapter ?, about the software used for the

implementation.

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CHAPTER - 2

IRIS RECOGNITION

2.1 INTRODUCTION:

The iris is an e%ternally visible, yet protected organ whose unique

epigenetic pattern remains stable throughout adult life. These characteristics ma(e it very

attractive for use as a biometric for identifying individuals. The purpose of


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CHAPTER - 3

IRIS SYSTEM IMPLEMENTATION

3.1 IMAGE AC9UISITION: #mage acquisition is considered the most critical step in the project

since all subsequent stages depend highly on the image quality. #n order to accomplish

this, we use a 9 camera. ;e set the resolution to ?>'%>G', the type of the image to

jpeg, and the mode to white and blac( for greater details. The camera is situated normally

between half a meter to one meter from the subject. *3 to )' inches+

The 9cameras job is to ta(e the image from the optical system and

convert it into electronic data. 5ind the iris image by a monochrome 9 *harged

couple 9evice+ camera transfer the value of the different pi%els out of the 9 chip.

-ead out the voltages from the 9chip. Thereafter the signals of each data are

amplified and sent to an A9 *Analog to 9igital onverter+.

5igs 3.) B": 9#A7-A! 5 #!A7/ AC#8#T# 8#7 9 A!/-A

3.2 IMAGE MANIPULATION:

#n the preprocessing stage, we transformed the images from -7B to gray

level and from eightbit to double precision thus facilitating the manipulation of the

images in subsequent steps.

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8o the first problem encountered with modeling this biological process is

that of defining, precisely, what an edge might be. The usual approach is to simply define

edges as step discontinuities in the image signal. The method of locali$ing these

discontinuities often then becomes one of finding local ma%ima in the derivative of the

signal, or $erocrossings in the second derivative of the signal.

#n computer vision, edge detection is traditionally implemented by

convolving the signal with some form of linear filter, usually a filter that appro%imates a

first or second derivative operator. An odd symmetric filter will appro%imate a first

derivative, and pea(s in the convolution output will correspond to edges *luminance

discontinuities+ in the image.

An even symmetric filter will appro%imate a second derivative operator.

Kerocrossings in the output of convolution with an even symmetric filter will correspond

to edges0 ma%ima in the output of this operator will correspond to tangent discontinuities,

often referred to as bars or lines.

3.5 CANNY EDGE DETECTOR:

/dges characteri$e boundaries and are therefore a problem of fundamental

importance in image processing. /dges in images are areas with strong intensity contrasts

H a jump in intensity from one pi%el to the ne%t. /dge detecting an image significantly

reduces the amount of data and filters out useless information, while preserving the

important structural properties in an image.

The anny edge detection algorithm is (nown to many as the optimal edge

detector. A list of criteria to improve current methods of edge detection is the first and

most obvious is low error rate. #t is important that edges occurring in images should not

be missed and that there be responses to nonedges. The second criterion is that the

edge points be well locali$ed. #n other words, the distance between the edge pi%els as

found by the detector and the actual edge is to be at a minimum. A third criterion is to

have only one response to a single edge. This was implemented because the first 2 were

not substantial enough to completely eliminate the possibility of multiple responses to an

edge.

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S"!1 :

#n order to implement the canny edge detector algorithm, a series of steps must

be followed. The first step is to filter out any noise in the original image before trying to

locate and detect any edges. And because the 7aussian filter can be computed using a

simple mas(, it is used e%clusively in the anny algorithm. nce a suitable mas( has

been calculated, the 7aussian smoothing can be performed using standard convolution

methods. The 7aussian mas( used is shown below.

S"!2:

After smoothing the image and eliminating the noise, the ne%t step is to find the

edge strength by ta(ing the gradient of the image. The 8obel operator performs a 29

spatial gradient measurement on an image. Then, the appro%imate absolute gradient

magnitude *edge strength+ at each point can be found. The 8obel operator uses a pair of

3%3 convolution mas(s, one estimating the gradient in the %direction *columns+ and the

other estimating the gradient in the ydirection *rows+.

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They are shown belowI

The magnitude, or /97/ 8T-/7T6, of the gradient is then

appro%imated using the formulaI

L7L M L7%L N L7yL

3.; HOUGH TRANSFORM:

The 6ough transform is a technique which can be used to isolate features of

a particular shape within an image. Because it requires that the desired features be

specified in some parametric form, the classical 6ough transform is most commonly used

for the detection of regular curves such as lines, circles, ellipses, etc. A generali$ed

6ough transform can be employed in applications where a simple analytic description ofa feature*s+ is not possible. 9ue to the computational comple%ity of the generali$ed

6ough algorithm, we restrict the main focus of this discussion to the classical 6ough

transform.

9espite its domain restrictions, the classical 6ough transform *hereafter

referred to without the classical prefi%+ retains many applications0 as most manufactured

parts contain feature boundaries which can be described by regular curves. The main

advantage of the 6ough transform technique is that it is tolerant of gaps in feature

boundary descriptions and is relatively unaffected by image noise.

The 6ough transform is computed by ta(ing the gradient of the original

image and accumulating each non$ero point from the gradient image into every point

that is one radius distance away from it.

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That way, edge points that lie along the outline of a circle of the given radius

all contribute to the transform at the center of the circle, and so pea(s in the transformed

image correspond to the centers of circular features of the given si$e in the original

image. nce a pea( is detected and a circle OfoundO at a particular point, nearby points

*within onehalf of the original radius+ are e%cluded as possible circle centers to avoid

detecting the same circular feature repeatedly.

5ig 3.2I 6ough

circle detection

with gradientinformation.

ne

way of reducing

the computation required to perform the 6ough transform is to ma(e use of gradient

information which is often available as output from an edge detector. #n the case of the

6ough circle detector, the edge gradient tells us in which direction a circle must lie from

a given edge coordinate point.

The 6ough transform can be seen as an efficient implementation of a

generali$ed matched filter strategy. #n other words, if we created a template composed of

a circle of )Os *at a fi%ed + and 'Os everywhere else in the image, then we could convolve

it with the gradient image to yield an accumulator arrayli(e description of all the circles

of radius in the image. 8how formally that the basic 6ough transforms * i.e. the

algorithm with no use of gradient direction information+ is equivalent to templatematching.

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*3.3.)+ *3.3.2+ *3.3.3+ *3.3.>+

5ig 3.3 /97/ !A8I

3.3.)+ an eye image 3.3.2+ corresponding edge map 3.3.3+ edge map with only hori$ontal

gradients 3.3.>+ edge map with only vertical gradients.

3.= NORMALISATION:

nce the iris region is successfully segmented from an eye image, the ne%t

stage is to transform the iris region so that it has fi%ed dimensions in order to allow

comparisons. The dimensional inconsistencies between eye images are mainly due to thestretching of the iris caused by pupil dilation from varying levels of illumination. ther

sources of inconsistency include, varying imaging distance, rotation of the camera, head

tilt, and rotation of the eye within the eye soc(et. The normalisation process will produce

iris regions, which have the same constant dimensions, so that two photographs of the

same iris under different conditions will have characteristic features at the same spatial

location. Another point of note is that the pupil region is not always concentric within the

iris region, and is usually slightly nasal. This must be ta(en into account if trying to

normali$e the


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UN7RAPPING

4.1 INTRODUCTION:

#mage processing of the iris region is computationally e%pensive. #n additionthe area of interest in the image is a OdonutO shape, and grabbing pi%els in this region

requires repeated rectangulartopolar conversions. To ma(e things easier, the iris region

is first unwrapped into a rectangular region using simple trigonometry. This allows the

iris decoding algorithm to address pi%els in simple *row, column+ format.

4.2 ASYMMETRY OF THE EYE:

Although the pupil and iris circles appear to be perfectly concentric, they rarely

are. #n fact, the pupil and iris regions each have their own bounding circle radius and

center location. This means that the unwrapped region between the pupil and iris

bounding does not map perfectly to a rectangle. This is easily ta(en care of with a little

trigonometry. There is also the matter of the pupil, which grows and contracts its area to

control the amount of light entering the eye. Between any two images of the same

personOs eye, the pupil will li(ely have a different radius. ;hen the pupil radius changes,

the iris stretches with it li(e a rubber sheet. "uc(ily, this stretching is almost linear, and

can be compensated bac( to a standard dimension before further processing.

4.3 THE UN7RAPPING ALGORITHM:

#n fig >.), points p and i are the detected centers of the pupil and iris

respectively. ;e e%tend a wedge of angle dP starting at an angle P, from both points p

and i, with radii -p and -i, respectively. The intersection points of these wedges with

the pupil and iris circles form a s(ewed wedge polygon )23>. The s(ewed wedge is

subdivided radially into bloc(s and the image pi%el values in each bloc( are averaged

to form a pi%el *j,(+ in the unwrapped iris image, where j is the current angle number and

( is the current radius number.

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5ig >.)I Algorithm

for unwrapping the

iris region.

5or

this project, the

standard

dimensions of the

e%tracted iris

rectangle are )2G rows and G columns *see 5igure >.)+. This corresponds to M)2G

wedges, each of angle , with each wedge divided radially into G sections. The

equations below define the important points mar(ed in 5igure ). oints a through d are

interpolated along line segments )3 and 2>.

4.4 CONTRAST AD>USTMENT:

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5ig >.2I #mage before ontrast Adjustment

Fig 4.3: Image after Contrast Adjustment

otice that figures >.2 and >.3 appear to be better contrasted than figure >.)

These images have been equali$ed in contrast to ma%imi$e the range of luminance values

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in the iris image. This ma(es it numerically easier to encode the iris data. The equali$ing

is done by acquiring a luminance histogram of the image and stretching the upper and

lower boundaries of the histogram to span the entire range of luminance values '2&&.

5igure >.) demonstrates an e%ample of this process.

4.5 FEATURE E?TRACTION:

Qne of the most interesting aspects of the world is that it can be considered

to be made up of patterns. A pattern is essentially an arrangement. #t is characteri$ed by

the order of the elements of which it is made, rather than by the intrinsic nature of these

elementsR *obert ;iener+. This definition summari$es our purpose in this part. #n fact,

this step is responsible of e%tracting the patterns of the iris ta(ing into account the

correlation between adjacent pi%els. 5or this we use wavelets transform, and more

specifically the Q7abor 5ilteringR.

CHAPTER @ 5

7AVELET ANALYSIS

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5.1 GABOR FILTERING:

To understand the concept of 7abor filtering, we must first start with 7abor

wavelets. 7abor wavelets are formed from two components, a comple% sinusoidal carrier

and a 7aussian envelope.

g *%, y+ M s *%, y+ wr *%, y+

The comple% carrier ta(es the formI

s *%, y+ M e j*2S*u'%Nv'y+N+

;e can visuali$e the real and imaginary parts of this function separately as

shown in this figure. The real part of the function is given byI

-e *s *%, y++ M cos *2S *u'% N v'y+ N +

*&.&.)+ *&.&.2+

5ig &.) #!A7/ 8-/

&.&.)+-eal art &.&.2+#maginary art

and the imaginaryI

#m *s *%, y++ M sin *2 *u'% N v'y+ N +

The parameters u' and v' represent the frequency of the hori$ontal and vertical

sinusoids respectively. represents an arbitrary phase shift. The second component of a

7abor wavelet is its envelope. The resulting wavelet is the product of the sinusoidal

carrier and this envelope. The envelope has a 7aussian profile and is described by the

following equationI

g *%, y+ M :e S*a2*%U%'+r 2Nb2*yUy'+r 2+

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;hereI *% U %'+r M *% U %'+ cos *P+ N *y U y'+ sin *P+

*y U y'+r M U*% U %'+ sin *P+ N *y U y'+ cos *P+

The parameters used above areI

: a scaling constant

*a, b+ /nvelope a%is scaling constants,

P envelope rotation constant,

*%', y'+ 7aussian envelope pea(.

5ig &.2 7A88#A /@/"/

To put it all together, we multiply s *%, y+ by wr *%, y+. This produces a wavelet li(e this

oneI

5ig &.3 7AB- ;A@/"/T

5.2 GENERATING AN IRIS CODE:

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After performing unwrapping algorithm it maps the image to artesian coordinates so we

have something li(e the followingI

5ig &.> -""/9 #-#8

;hat we want to do is somehow e%tract a set of unique features from this iris

and then store them. That way if we are presented with an un(nown iris, we can compare

the stored features to the features in the un(nown iris to see if they are the same. ;eOll

call this set of features an V#ris ode.V

Any given iris has a unique te%ture that is generated through a random process

before birth. 5ilters based on 7abor wavelets turn out to be very good at detecting

patterns in images. ;eOll use a fi%ed frequency )9 7abor filter to loo( for patterns in our

unrolled image.

5irst, weOll ta(e a one pi%el wide column from our unrolled image and

convolve it with a )9 7abor wavelet. Because the 7abor filter is comple%, the result willhave real and imaginary parts which are treated separately. ;e only want to store a small

number of bits for each iris code, so the real and imaginary parts are each quanti$ed. #f a

given value in the result vector is greater than $ero, a one is stored0 otherwise $ero is

stored. nce all the columns of the image have been filtered and quanti$ed, we can form

a new blac( and white image by putting all of the columns side by side. The real and

imaginary parts of this image *a matri%+, the iris code, are shown hereI



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*&.&.)+ *&.&.2+

5ig &.& #!A7/ 5 #-#8 9/

&.&.)+ -/A" A-T &.&.2+ #!A7#A-E A-T

5.3 TEST OF STATISTICAL INDEPENDANCE:

This test enables the comparison of two iris patterns. This test is based on

the idea that the greater the 6amming distance between two feature vectors, the greater

the difference between them. Two similar irises will fail this test since the distance

between them will be small. #n fact, any two different irises are statistically QguaranteedR

to pass this test as already proven. The 6amming distance *69+ between two Boolean

vectors is defined as followsI

;here, A and B are the coefficients of two iris images and is the si$e of the feature

vector *in our case M D'2+. The is the (nown Boolean operator that gives a binary )

if the bits at position j in A and B are different and ' if they are similar.

5ig &.& 6A!!#7 9#8TA/8 A""AT#I



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CHAPTER - ;

MATLAB

;.1 INTRODUCTION: !AT"ABW is a highperformance language for technical computing. #t

integrates computation, visuali$ation, and programming in an easytouse environment

where problems and solutions are e%pressed in familiar mathematical notation. Typical

uses include

• !ath and computation

• Algorithm development

• 9ata acquisition

• !odeling, simulation, and prototyping

• 9ata analysis, e%ploration, and visuali$ation

• 8cientific and engineering graphics

• Application development, including graphical user interface

building.

!AT"AB is an interactive system whose basic data element is an

array that does not require dimensioning. This allows you to solve many technical

computing problems, especially those with matri% and vector formulations, in a

fraction of the time it would ta(e to write a program in a scalar non interactive

language such as or 5-T-A.

The name !AT"AB stands for matrix laboratory. !AT"AB was

originally written to provide easy access to matri% software developed by the

"#A: and /#8A: projects. Today, !AT"AB engines incorporate the"AA: and B"A8 libraries, embedding the state of the art in software for

matri% computation.

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!AT"AB features a family of addon applicationspecific solutions called

toolbo%es. @ery important to most users of !AT"AB, toolbo%es allow you to and apply

speciali$ed technology. Toolbo%es are comprehensive collections of !AT"AB functions

*!files+ that e%tend the !AT"AB environment to solve particular classes of problems.

Areas in which toolbo%es are available include signal processing, control systems, neural

networ(s, fu$$y logic, wavelets, simulation, and many others.

;.2 THE MATLAB SYSTEM:

The !AT"AB system consists of five main partsI

( DEVELOPMENT ENVIRONMENT:

This is the set of tools and facilities that help you use !AT"AB functions

and files. !any of these tools are graphical user interfaces. #t includes the !AT"AB

des(top and ommand ;indow, a command history, an editor and debugger, and

browsers for viewing help, the wor(space, files, and the search path.

, THE MATLAB MATHEMATICAL FUNCTION LIBRARY:

This is a vast collection of computational algorithms ranging from elementary

functions, li(e sum, sine, cosine, and comple% arithmetic, to more sophisticated functions

li(e matri% inverse, matri% /igen values, Bessel functions, and fast 5ourier transforms.

$ THE MATLAB LANGUAGE:

This is a highlevel matri%1array language with control flow statements,

functions, data structures, input1output, and objectoriented programming features. #t

allows both Vprogramming in the smallV to rapidly create quic( and dirty throwaway

programs, and Vprogramming in the largeV to create large and comple% application programs.

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0 GRAPHICS:

!AT"AB has e%tensive facilities for displaying vectors and matrices as

graphs, as well as annotating and printing these graphs. #t includes highlevel functions

for twodimensional and threedimensional data visuali$ation, image processing,

animation, and presentation graphics. #t also includes lowlevel functions that allow you

to fully customi$e the appearance of graphics as well as to build complete graphical user

interfaces on your !AT"AB applications.

! THE MATLAB APPLICATION PROGRAM INTERFACE:

This is a library that allows you to write and 5-T-A programs that

interact with !AT"AB. #t includes facilities for calling routines from !AT"AB

*dynamic lin(ing+, calling !AT"AB as a computational engine, and for reading and

writing !ATfiles.

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SOURCE CODE

function XB9, B;TY Mbandtrace *B;+B9 M XY0

B;T M B;0

8T M fndst *B;T+0

dir M X),)Y0

oint M 8T0

B9 M XB908TY0

e%t M oint N dir0

while *e%t*)+4e%t*2+MM'+ L *e%t*)+ZMsi$e*B;T,)++ L

*e%t*2+ZMsi$e*B;T,2++

dir M dirne%t*dir,'+0

e%t M oint N dir0

end

B;T*oint*)+,oint*2++ M '0

totle M sum*sum*B;T++0

i M )0j M '0

while *i[Mtotle+ \ **e%t*)+]M8T*)++ L *e%t*2+]M8T*2+++

if B;T*e%t*)+,e%t*2++ MM '

if j ZM G

e%t M oint0

brea(0

end

j M j N )0 dir M dirne%t*dir,'+0

e%t M oint N dir0

else

j M '0

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Oguiutput5cnO, _ircl9etectutput5cn, ...

Ogui"ayout5cnO, XY , ...

Oguiallbac(O, XY+0

if nargin \\ ischar*varargin`)+

gui8tate.guiallbac( M str2func*varargin`)+0

end

F /%ecutes just before ircl9etect is made visible.

function ircl9etectpening5cn*hbject, eventdata, handles, varargin+

F This function has no output args, see utput5cn.

F hbject handle to figure

F eventdata reserved to be defined in a future version of !AT"AB

F handles structure with handles and user data *see 7#9ATA+

F varargin command line arguments to ircl9etect *see @A-A-7#+

F hoose default command line output for ircl9etect

#mage M repmat*logical*uintG*'++,2'',2''+0


F handles empty handles not created until after all reate5cns called

F 6intI edit controls usually have a white bac(ground on ;indows.

F 8ee #8 and !T/-.

if ispc

set*hbject,OBac(groundolorO,OwhiteO+0

else

set*hbject,OBac(groundolorO,get*',OdefaulticontrolBac(groundolorO++0

end

F /%ecutes on slider movement.

function -ad8etallbac(*hbject, eventdata, handles+

F hbject handle to -ad8et *see 7B+



F 6intsI get*hbject,O@alueO+ returns position of slider

F get*hbject,O!inO+ and get*hbject,O!a%O+ to determine range of slider

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set*handles.te%t-,OstringO,get*hbject,O@alueO++0

F /%ecutes during object creation, after setting all properties.

function -ad8etreate5cn*hbject, eventdata, handles+




F 6intI slider controls usually have a light gray bac(ground, change

F OusewhitebgO to ' to use default. 8ee #8 and !T/-.

usewhitebg M )0

if usewhitebg

set*hbject,OBac(groundolorO,X.J .J .JY+0

else


end

F /%ecutes on button press in pushbutton).

function pushbutton)allbac(*hbject, eventdata, handles+

F hbject handle to pushbutton) *see 7B+



M /locate*handles.#mage,Xhandles.set0handles.setEY+0

set*handles.-ad9et,O8tringO,*3++0


function pushbutton2allbac(*hbject, eventdata, handles+




close*gcf+0

function -ad9etallbac(*hbject, eventdata, handles+




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F 6intsI get*hbject,O8tringO+ returns contents of -ad9et as te%t

F str2double*get*hbject,O8tringO++ returns contents of -ad9et as a double


function -ad9etreate5cn*hbject, eventdata, handles+





F 8ee #8 and !T/-.

if ispc


else


end

F /%ecutes on button press in pb8et.

function pb8etallbac(*hbject, eventdata, handles+

F hbject handle to pb8et *see 7B+



handles.set M str2double*get*handles.ent,O8tringO++0

handles.setE M str2double*get*handles.entE,O8tringO++0

handles.set- M get*handles.-ad8et,O@alueO+0

handles.#mage M handles.#mage4'0

outputcoord M plotcircle*handles.set,handles.setE,handles.set-+0

for iM)Isi$e*outputcoord,)+

handles.#mage*round*outputcoord*i,2++,round*outputcoord*i,)+++ M )0

end

a%es*handles.a%es)+0

imshow*handles.#mage+0

guidata*hbject, handles+0

function Xe%tdirYMdirne%t*dir,step+

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if stepMM'

dirMXX),)YO,X),'YO,X),)YO,X',)YO,X),)YO,X),'YO,X),)YO,X',)YOY0

for i M )IG

if dirO MM dir*I,i+

try e%tdirMdir*I,iN)+0

catch e%tdirMdir*I,)+0

end

e%tdirMe%tdirO0

end

end

elseif stepMM)

dirEMXX),)YO,X),)YO,X),)YO,X),)YO0X),'YO,X',)YO,X),'YO,X',)YOY0

9*i,j+Msqrt**dataset)*i,)+dataset)*j,)++^2N*dataset)*i,2+dataset)*j,2++^2+0

end

end

end

case 2

Xm),n)YMsi$e*dataset)+0

Xm2,n2YMsi$e*dataset2+0

9M$eros*m),m2+0

for iM)Im)

waitbar*i1m)+

for jM)Im2

9*i,j+Msqrt**dataset)*i,)+ dataset2*j,)++^2N*dataset)*i,2+ dataset2*j,2++^2+0

end

end

otherwise

error*Oonly one or two input argumentsO+

end

close*h+

function 9M/uclidian*dataset),dataset2+



33/60

h M waitbar*',O9istance omputationO+0

switch nargin

case )


m2Mm)0

9M$eros*m),m2+0

for iM)Im)

waitbar*i1m)+

for jM)Im2

if iMMj

9*i,j+Ma0

else

9*i,j+Msqrt**dataset)*i,)+dataset)*j,)++^2N*dataset)*i,2+

dataset)*j,2++^2+0

end

end

end

case 2


Xm2,n2YMsi$e*dataset2+0

9M$eros*m),m2+0

for iM)Im)

waitbar*i1m)+

for jM)Im2

9*i,j+Msqrt**dataset)*i,)+ dataset2*j,)++^2N*dataset)*i,2+

dataset2*j,2++^2+0

end

end

otherwise

error*Oonly one or two input argumentsO+

end



34/60

close*h+

function X8TY M fndst*B;+

s$ M si$e*B;+0

r M '0c M '0

sign M '0

for i M ) I s$*)+

for j M ) I s$*2+

if B;*i,j+ MM )

r M i0c M j0

sign M )0

brea(0

end

end

if sign MM ),brea(,end

end

if *rMM'+ L *cMM'+

error*OThere is no white point in VB;V.O+0

else

8T M Xr,cY0

/nd

function X,6!YM6oughcircle*B;,-p+

F676#-"/ detects circles in a binary image.

# M B;0

Xsy,s%YMsi$e*#+0

Xy,%YMfind*#+0

totalpi% M length*%+0

6!tmp M $eros*sy4s%,)+0

b M )Isy0

a M $eros*sy,totalpi%+0

if nargin MM )

-min M )0

T-- ollege of /ngineering 3>


35/60

-ma% M ma%*ma%*%+,ma%*y++0

else

-min M -p*)+0

-ma% M -p*2+0

end

y M repmat*yO,Xsy,)Y+0

% M repmat*%O,Xsy,)Y+0

6 M '0

for - M -min I -ma%

-2 M -^20

b) M repmat*bO,X),totalpi%Y+0

b2 M b)0

a) M *round*% sqrt*-2 *y b)+.^2+++0

a2 M *round*% N sqrt*-2 *y b2+.^2+++0

b) M b)*imag*a)+MM' \ a)Z' \ a)[s%+0

a) M a)*imag*a)+MM' \ a)Z' \ a)[s%+0

b2 M b2*imag*a2+MM' \ a2Z' \ a2[s%+0

a2 M a2*imag*a2+MM' \ a2Z' \ a2[s%+0

ind) M sub2ind*Xsy,s%Y,b),a)+0

ind2 M sub2ind*Xsy,s%Y,b2,a2+0

ind M Xind)0 ind2Y0

val M ones*length*ind+,)+0

dataMaccumarray*ind,val+0

6!tmp*)Ilength*data++ M data0

6!2tmp M reshape*6!tmp,Xsy,s%Y+0

Fimshow*6!2,XY+0

ma%val M ma%*ma%*6!2tmp++0

if ma%valZ6

6 M ma%val0

6! M 6!2tmp0

-c M -0

T-- ollege of /ngineering 3&


36/60

end

end

XB,AY M find*6!MM6+0

M Xmean*A+,mean*B+,-cY0

function varargout M hough7#*varargin+

F 6767# !file for hough7#.fig

F 6767#, by itself, creates a new 6767# or raises the e%isting

F singleton4.

F Begin initiali$ation code 9 T /9#T

gui8ingleton M )0

gui8tate M struct*OguiameO, mfilename, ...

Ogui8ingletonO, gui8ingleton, ...

Oguipening5cnO, _hough7#pening5cn, ...

Oguiutput5cnO, _hough7#utput5cn, ...


Oguiallbac(O, XY+0



end

if nargout

Xvarargout`)InargoutY M guimainfcn*gui8tate, varargin`I+0

else

guimainfcn*gui8tate, varargin`I+0

end

F /nd initiali$ation code 9 T /9#T

F /%ecutes just before hough7# is made visible.

function hough7#pening5cn*hbject, eventdata, handles, varargin+

F This function has no output args, see utput5cn.




T-- ollege of /ngineering 3?


37/60

F varargin command line arguments to hough7# *see @A-A-7#+

F hoose default command line output for hough7#

handles.output M hbject0

8 M repmat*logical*uintG*'++,>'',>''+0

outputcoord M plotcircle*2'',2'',D&+0

for iM)Isi$e*outputcoord,)+

8*round*outputcoord*i,2++,round*outputcoord*i,)+++ M )0

end


imshow*8+0

handles.8 M 80

F pdate handles structure


F #;A#T ma(es hough7# wait for user response *see #-/8!/+

F uiwait*handles.figure)+0

F utputs from this function are returned to the command line.

function varargout M hough7#utput5cn*hbject, eventdata, handles+

F varargout cell array for returning output args *see @A-A-7T+0




F 7et default command line output from handles structure

varargout`) M handles.output0

F /%ecutes on button press in pb"oad.

function pb"oadallbac(*hbject, eventdata, handles+

F hbject handle to pb"oad *see 7B+



Xfilename, pathnameY M uigetfile*`O4.bmpO0O4.jpgO0O4.tifO+0

8 M imread*Xpathname filenameY+0

handles.8 M 80

T-- ollege of /ngineering 3D


38/60


imshow*8+0



F /%ecutes on button press in pb9etect.

function pb9etectallbac(*hbject, eventdata, handles+

F hbject handle to pb9etect *see 7B+



- M get*handles.sld-,O@alueO+0

X,6!Y M 6oughcircle*handles.8,X-,-Y+0

Xma%val,ma%indY M ma%*ma%*6!++0

a%es*handles.a%es2+0

imshow*6!+0


imshow*handles.8+0hold on0

outputcoord M plotcircle**)+,*2+,*3++0

plot*outputcoord*I,)+,outputcoord*I,2++0

plot**)+,*)+,Or4O+0hold off0

set*handles.t%t,OstringO,*)++0

set*handles.t%tE,OstringO,*2++0

set*handles.t%t@al,OstringO,ma%val+0

F /%ecutes on slider movement.

function sld-allbac(*hbject, eventdata, handles+

F hbject handle to sld- *see 7B+



F 6intsI get*hbject,O@alueO+ returns position of slider

F get*hbject,O!inO+ and get*hbject,O!a%O+ to determine range of slider

set*handles.t%t-,OstringO,get*hbject,O@alueO++0


T-- ollege of /ngineering 3G


39/60

function sld-reate5cn*hbject, eventdata, handles+

function t%t@alallbac(*hbject, eventdata, handles+

F hbject handle to t%t@al *see 7B+



F 6intsI get*hbject,O8tringO+ returns contents of t%t@al as te%t

F str2double*get*hbject,O8tringO++ returns contents of t%t@al as a double


function t%t@alreate5cn*hbject, eventdata, handles+

F hbject handle to t%t@al *see 7B+




F 8ee #8 and !T/-.

if ispc \\ isequal*get*hbject,OBac(groundolorO+,

get*',OdefaulticontrolBac(groundolorO++


end

F /%ecutes on button press in pb-eturn.

function pb-eturnallbac(*hbject, eventdata, handles+

F hbject handle to pb-eturn *see 7B+



F lose urrent figure window.

close*gcf+0

function XB;YMim2bwt*#,t+

if nargin MM )

t M tautoset*#+0

end

s$Msi$e*#+0

B;Mrepmat*logical*uintG*'++,s$*)+,s$*2++0

T-- ollege of /ngineering 3J


40/60

for r M 3 I s$*)+2

for c M 3 I s$*2+2

if #*r,c+[t

if *#*r),c)+[t+\*#*r),c+[t+\*#*r),cN)+[t+\*#*r,c

)+[t+\*#*r,cN)+[t+\*#*rN),c)+[t+\*#*rN),c+[t+\*#*rN),cN)+[t+

B;*r,c+ M '0

else

B;*r,c+ M )0

end

else

B;*r,c+ M '0

end

end

end

for r M ) I s$*)+

B;*r,)I2+ M '0

B;*r,*si$e*B;,2+)+Isi$e*B;,2++ M '0

end

for c M ) I s$*2+

B;*)I2,c+ M '0

B;**si$e*B;,)+)+Isi$e*B;,)+,c+ M '0

end

function varargout M #ris"ocat*varargin+

F #-#8"AT !file for #ris"ocat.fig

F

gui8ingleton M )0

gui8tate M struct*OguiameO, mfilename, ...

Ogui8ingletonO, gui8ingleton, ...

Oguipening5cnO, _#ris"ocatpening5cn, ...

Oguiutput5cnO, _#ris"ocatutput5cn, ...


T-- ollege of /ngineering >'


41/60

Oguiallbac(O, XY+0



end

if nargout

Xvarargout`)InargoutY M guimainfcn*gui8tate, varargin`I+0

else

guimainfcn*gui8tate, varargin`I+0

end

F /%ecutes just before #ris"ocat is made visible.

function #ris"ocatpening5cn*hbject, eventdata, handles, varargin+


F #;A#T ma(es #ris"ocat wait for user response *see #-/8!/+

F uiwait*handles.figure)+0

F utputs from this function are returned to the command line.

function varargout M #ris"ocatutput5cn*hbject, eventdata, handles+

F varargout cell array for returning output args *see @A-A-7T+0




F 7et default command line output from handles structure

varargout`) M handles.output0

function edit3allbac(*hbject, eventdata, handles+

F hbject handle to edit3 *see 7B+



F 6intsI get*hbject,O8tringO+ returns contents of edit3 as te%t

F str2double*get*hbject,O8tringO++ returns contents of edit3 as a double


function edit3reate5cn*hbject, eventdata, handles+


T-- ollege of /ngineering >)


42/60




F 8ee #8 and !T/-.

if ispc


else


end

function edit2allbac(*hbject, eventdata, handles+




F 6intsI get*hbject,O8tringO+ returns contents of edit2 as te%t

F str2double*get*hbject,O8tringO++ returns contents of edit2 as a double


function edit2reate5cn*hbject, eventdata, handles+





F 8ee #8 and !T/-.

if ispc


else


end

function edit?allbac(*hbject, eventdata, handles+

F hbject handle to edit? *see 7B+



T-- ollege of /ngineering >2


43/60

F 6intsI get*hbject,O8tringO+ returns contents of edit? as te%t

F str2double*get*hbject,O8tringO++ returns contents of edit? as a double


function edit?reate5cn*hbject, eventdata, handles+

F hbject handle to edit? *see 7B+




F 8ee #8 and !T/-.

if ispc


else


end

function edit&allbac(*hbject, eventdata, handles+

F hbject handle to edit& *see 7B+



function edit&reate5cn*hbject, eventdata, handles+

F hbject handle to edit& *see 7B+




F 8ee #8 and !T/-.

if ispc


else


end

function edit>allbac(*hbject, eventdata, handles+

F hbject handle to edit> *see 7B+

T-- ollege of /ngineering >3


44/60



F 6intsI get*hbject,O8tringO+ returns contents of edit> as te%t

F str2double*get*hbject,O8tringO++ returns contents of edit> as a double


function edit>reate5cn*hbject, eventdata, handles+

F hbject handle to edit> *see 7B+




F 8ee #8 and !T/-.

if ispc


else


end


function pushbutton)allbac(*hbject, eventdata, handles+




Xfilename, pathnameY M uigetfile*`O4.bmpO0O4.jpgO0O4.tifO+0

8 M imread*Xpathname filenameY+0

if isrgb*8+

8 M rgb2gray*8+0

end

F8Mresi$eu2*8,'.G,'.G+0

handles.8 M 80


imshow*8+0


T-- ollege of /ngineering >>


45/60


F /%ecutes on button press in pushbutton2.

function pushbutton2allbac(*hbject, eventdata, handles+

F hbject handle to pushbutton2 *see 7B+



B; M im2bwt*handles.8+0

B; M bandtrace*B;+0

tic0

M 6oughcircle*B;+0

t) M toc0

set*handles.te%tT),OstringO,t)+0

handles. M 0

set*handles.edit),OstringO,*)++0

set*handles.edit2,OstringO,*2++0

set*handles.edit3,OstringO,*3++0


imshow*handles.8+0 hold on0

plot**)+,*2+,O%rO+0

outputcoord M plotcircle**)+,*2+,*3++0


hold off0

M handles.

B; M ]*im2bw*handles.8++0

enter M X*)+0*2+Y0

for i M & I &

for j M & I &

ent M X*)+Ni0*2+NjY0

enter M Xenter,entY0

end

end

T-- ollege of /ngineering >&


46/60

tic0

) M /locate*B;,enter,*3++0

t2 M toc0

set*handles.te%tT2,OstringO,t2+0

handles.) M )0

set*handles.edit>,OstringO,)*)++0

set*handles.edit&,OstringO,)*2++0

set*handles.edit?,OstringO,)*3++0


imshow*handles.8+0 hold on0

plot*)*)+,)*2+,O4gO+0

outputcoord M plotcircle*)*)+,)*2+,)*3++0


hold off0



F /%ecutes on button press in pushbutton>.

function pushbutton>allbac(*hbject, eventdata, handles+

F hbject handle to pushbutton> *see 7B+



fig M hough7#0

fig2handles M guihandles*fig+0

handles.figure2 M fig2handles0



F /%ecutes on button press in pushbutton?.

function pushbutton?allbac(*hbject, eventdata, handles+

F hbject handle to pushbutton? *see 7B+



T-- ollege of /ngineering >?


47/60

a%es*handles.a%es)+0imshow*X2&&Y+0

a%es*handles.a%es2+0imshow*X2&&Y+0

a%es*handles.a%es3+0imshow*X2&&Y+0

set*handles.edit),OstringO,OO+0

set*handles.edit2,OstringO,OO+0

set*handles.edit3,OstringO,OO+0

set*handles.edit>,OstringO,OO+0

set*handles.edit&,OstringO,OO+0

set*handles.edit?,OstringO,OO+0

set*handles.te%tT),OstringO,OO+0

set*handles.te%tT2,OstringO,OO+0

if isfield*handles,O8O+

handles.8 M XY0

end

if isfield*handles,OO+

handles. M XY0

end

if isfield*handles,O)O+

handles.) M XY0

end



F /%ecutes on button press in pushbuttonD.

function pushbuttonDallbac(*hbject, eventdata, handles+

F hbject handle to pushbuttonD *see 7B+



if isfield*handles,Ofigure2O+

if ishandle*handles.figure2.figure)+

close*handles.figure2.figure)+0

T-- ollege of /ngineering >D


48/60


49/60

function pushbutton)2allbac(*hbject, eventdata, handles+

F hbject handle to pushbutton)2 *see 7B+



B; M im2bwt*handles.8+0

B; M bandtrace*B;+0

tic0

M 6oughcircle*B;+0

8T M fndst*B;+0

prompt M `O/nter file nameIO0

dlgtitle M O#nput for -adii e%portO0

numlines M )0

def M `O9avidO0

answer M inputdlg*prompt,dlgtitle,numlines,def+0

saveradii*answer`),,8T+0


function a%es3reate5cn*hbject, eventdata, handles+

F hbject handle to a%es3 *see 7B+



F 6intI place code in pening5cn to populate a%es3

function XB9im,B9YMbandtrace*B;+

B9 M XY0

B;Ttm M B;0

B9imMrepmat*logical*uintG*'++,si$e*B;,)+,si$e*B;,2++0

while sum*sum*B;Ttm++ ]M '

XB9tm,B;TtmY M bandtrace*B;Ttm+0

if length*B9+ [ length*B9tm+

B9 M B9tm0

end

T-- ollege of /ngineering >J


50/60


51/60

if C ZM '.&4totle

brea(0

end

end

r M r N deltar0

end

end

C M '0

for r M *3+deltar12 I *3+Ndeltar12

Ct M cirquad*B;,*)+,*2+,r,)+0

if C [ Ct

C M Ct0

*3+ M r0

Fbrea(0

end

end

F

F #nputs I

F The coordinates of the center of this circle

F E The E coordinates of the center of this circle

F -adius The radius of this circle ZM '

F intervals *optional+ The number of evenly spaced points along the a%is

F inclusive of the start and end coordinates

F *needed by OintervalO algorithm+

function outputcoord M plotcircle*,E,-adius,varargin+

output M XY0

outputE M XY0

tempmod M )0

calmode M OangleO0 Fdefault

intervals M a0

T-- ollege of /ngineering &)


52/60

F

MMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMM

F hec( optional inputs

F


if *length*varargin+ Z '+

for a M )I)Ilength*varargin+

if isstr*vararginà+ MM )

if **strcmp*vararginà,OangleO+ MM )+L...

*strcmp*vararginà,OintervalO+ MM )+L...

*strcmp*vararginà,ObresenhamO+ MM )+L...

*strcmp*vararginà,Obresenham8olidO+ MM )+...

+

calmode M vararginà0

end

elseif isfinite*vararginà+ MM )

intervals M vararginà0

else

error*O#nvalid argumentsO+0

end

end

end

F


F #nitiali$ation of OintervalO

F


if strcmp*calmode,OintervalO+ MM )

T-- ollege of /ngineering &2


53/60

F 8atisfies requirement for calculation by the given intervals

if isnan*intervals+ MM )

error*Oo interval givenO+0

end

tempmod M mod*intervals,2+0

interval M *intervals tempmod+ 1 20

intervalsi$e M *-adiusN-adius+1intervals0

value M '0

if tempmod MM )

output M X'Y0

outputE M X-adiusY0

else

value M *)12+4intervalsi$e0

end

calmode M OintervalO0

end


F alculate the )st quardrant

F


F 444444444444444444444444444444444444444444444444444444444444

F by the angle, scaled by the given radius

F 444444444444444444444444444444444444444444444444444444444444

if strcmp*calmode,OangleO+ MM )

incrementangle M pi4*)1-adius+0

currangle M pi120

loopM'0

while currangleZ'

loopMloopN)0

output M Xoutput*I+0sqrt*-adius^2*-adius4sin*currangle++^2+Y0

outputE M XoutputE*I+0sqrt*-adius^2*-adius4cos*currangle++^2+Y0

T-- ollege of /ngineering &3


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currangle M currangleincrementangle0

end

output M Xoutput*I+0-adiusY0

outputE M XoutputE*I+0'Y0

elseif strcmp*calmode,OintervalO+ MM )

F 444444444444444444444444444444444444444444444444444444444444

F by the given %interval

F 444444444444444444444444444444444444444444444444444444444444

value M value N intervalsi$e0

while value [ -adius

output M Xoutput*I+0valueY0

outputE M XoutputE*I+0sqrt**-adius4-adius+*value4value++Y0

value M value N intervalsi$e0

end

output M Xoutput*I+0-adiusY0

outputE M XoutputE*I+0'Y0

elseif *strcmp*calmode,ObresenhamO+ MM )+ L *strcmp*calmode,Obresenham8olidO+ MM

)+

M round*+0

E M round*E+0

-adius M round*-adius+0

F 444444444444444444444444444444444444444444444444444444444444

%i M '0

yi M -adius0

thetaiM24*)-adius+0

"imit M '0

while yi ZM "imit

F 8et i%el

if *strcmp*calmode,ObresenhamO+ MM )+

F lot the circumference

T-- ollege of /ngineering &>


55/60

output M Xoutput*I+0%iY0

outputE M XoutputE*I+0yiY0

elseif *strcmp*calmode,Obresenham8olidO+ MM )+

F reate a solid circle

tempE M X'I)IyiYO0

temp M tempE0

temp*I+ M %i0

output M Xoutput*I+0tempY0

outputE M XoutputE*I+0tempEY0

else

error*O#nvalid optionO+0

end

F determine if case ) or 2, > or &, or 3

if thetai [ '

delta M 24*thetai N yi+ )0

F determine whether case ) or 2

if delta [M '

F move hori$ontally

%i M %i N )0

thetai M thetai N *24%i+ N )0

else

F move diagonally

%i M %i N )0

yi M yi )0

thetai M thetai N *24*%i yi++ N 20

end

elseif thetai Z '

end

elseif thetai MM '

F move diagonally

T-- ollege of /ngineering &&


56/60

%i M %i N )0

yi M yi )0

thetai M thetai N *24*%i yi++ N 20

end

end

end


F alculate the 2nd quardrant

F


lengthoutput M length*output+0

if tempmod MM )

F Avoids duplicate coordinates

output M Xoutput*XlengthoutputI)I2Y+4*)+0output*I+Y0

outputE M XoutputE*XlengthoutputI)I2Y+0outputE*I+Y0

else

output M Xoutput*XlengthoutputI)I)Y+4*)+0output*I+Y0

outputE M XoutputE*XlengthoutputI)I)Y+0outputE*I+Y0

end


F 8hift the circle to the desired center

F


output M outputN0

outputE M outputENE0

outputcoord M Xoutput,outputEY0

F #f a solid is as(ed for ma(e sure there are no duplicates

if *strcmp*calmode,Obresenham8olidO+ MM )+

outputcoord M unique*outputcoord,OrowsO+0

T-- ollege of /ngineering &?


57/60

end

function recogni$e

dat)Minput*Oenter the path of te%t file )O+0

dat2Minput*Oenter the path of te%t file 2O+0

a M te%tread*dat) , OFsO, OwhitespaceO, O O +0

b M te%tread*dat2 , OFsO, OwhitespaceO, O O +0

FdM/uclidian*a,b+0

if *cell2mat*a*J,)++]Mcell2mat*b*J,)+++

disp*O#-#8 does not matches with the current personO+0

else if *cell2mat*a*)',)++]Mcell2mat*b*)',)+++

disp*O#-#8 does not matches with the current personO+ 0

else

disp*O#-#8 9/8 !AT6/8 ;#T6 T6/ --/T /-8O+0

end

end

function saveradii*name,,8T+

nameMstrrep*name,O O,OO+0

dateMdatestr*now,2J+0

5ileameMXname OO date O.t%tOY0

fileMfopen*5ileame,OwtO+0

fprintf*file,OF2.'f nO,si$e*,)++0

fprintf*file,OFsO,O-adiusI O+0

fprintf*file,OF2.'f nO,X8TY+0

fprintf*file,OFs nO,OO+0

fprintf*file,OFs nO,OO+0

fclose*file+0

function XTYMtautoset*#+

F#Mimread*Oeye.jpgO+

graycountMimhist*#+0

s$Msi$e*#+0

TM'0

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graycountMfilter*X'.& ' '.&Y,),graycount+0

Ffigure,imhist*#+0

diffcntMdiff*graycount+0

prema% M graycount*)+0

for i M 2 I *length*diffcnt+)+

if *graycount*i+Zgraycount*i)++\*graycount*iN)+[graycount*i++\*diffcnt*i

)+Z'+\*diffcnt*iN)+['+

F

prema%Mma%*graycount*i+,prema%+0

continue0

end

if *graycount*i+[graycount*i)++\*graycount*iN)+Zgraycount*i++\*diffcnt*i

)+['+\*diffcnt*iN)+Z'+\*graycount*i+['.D&4prema%+\*prema%1*s$*)+4s$*2++Z'.'

'2&+

TMi0

brea(0

end

end

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CONCLUSION

;e have successfully developed a new #ris -ecognition system capable of

comparing two digital eyeimages. This identification system is quite simple requiring

few components and is effective enough to be integrated within security systems that

require an identity chec(. The errors that occurred can be easily overcome by the use of

stable equipment. udging by the clear distinctiveness of the iris patterns we can e%pect

iris recognition systems to become the leading technology in identity verification.

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BIBLOGRAPHY

• QThe Biometrics technologyR Third /dition.

by 7uodong 7uo.

• Q#-#8 -ecognitionR 8econd /dition.

by -oy :aushi( and rabir Bhattacharya.

• QThe #-#8 -ecognition 8ystemR

by (shvi( 9ouglas.

• QBiometric systemsR

by ;ayle ;olf

• www.alibris.com

• www.adaptiveoptics.org

• www.icdri.org

• www.sans.org

• www.google.co.in

• www.wi(ipedia.com
http://www.alibris.com/http://www.adaptiveoptics.org/http://www.icdri.org/http://www.sans.org/http://www.google.co.in/http://www.wikipedia.com/http://www.alibris.com/http://www.adaptiveoptics.org/http://www.icdri.org/http://www.sans.org/http://www.google.co.in/http://www.wikipedia.com/

Documents

20051739 Iris Recongition