Iris

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IRIS- RECOGNITION SYSTEM

NEETHU SUNNY

MBA INTERNATIONA BUSINESS SCHOOL OF MANAGEMENT STUDIES CUSAT, KOCHI-22 Email: [email protected]

Abstract: Iris Recognition System is used for identifying a person using IRIS pattern match. IRIS is different in person to person .No two persons have the same IRIS pattern. So by IRIS pattern we can identify the persons . Key Words: BIOMETRICS, IRIS RECONITION SYSTEM & NORMALIZATION

1.0 INRODUCTION

In today’s information age it is not difficult to collect data about an individual and use that information to exercise control over the individual. Individuals generally do not want others to have personal information about them unless they decide to reveal it. With the rapid development of technology, it is more difficult to maintain the levels of privacy citizens knew in the past. In this context, data security has become an inevitable feature. Conventional methods of identification based on possession of ID cards or exclusive knowledge like social security number or a password are not altogether reliable. Biometric technology has now become a viable alternative to traditional identification systems because of its tremendous accuracy and speed. Biometric system automatically verifies or recognizes the identity of a living person based on physiological or behavioral characteristics. Since the persons to be identified should be physically present at the point of identification, biometric techniques gives high security. Iris is the focus of a relatively new means of biometric identification. The iris is called the living password because of its unique, random features. It is always with you and can not be stolen or faked. The iris of each eye is absolutely unique. The probability that any two irises could be alike is one in 10 to 78 powers — the entire human population of the earth is roughly 5.8 billion. So no two irises are alike in their details, even among identical twins. Even the left and right irises of a single person seem to be highly distinct. Every iris has a highly detailed and unique texture that remains stable over decades of life. Because of the texture, physiological nature and random generation of an iris artificial duplication is virtually impossible.

2.0 BIOMETRIC
Authentication is the process of verifying that a user requesting a network resource is who he, she, or it claims to be, and vice versa. Biometric authentication uses personal featuressomething that you are.Exciting Biometrics:

2.1 Fingerprint Recognition

This relies on the fact that a fingerprint’s uniqueness can be defined by analyzing the minutiae of a human being.Two individuals having the same fingerprint is less than one in a billion. 2.2 Voice Recognition

The person to be identified is usually pronounce a designated password or phrase, which facilitates the verification process.But has the weakness of technology 2.3 Signature Recognition This is done by analyzing the shape, speed, stroke, pen pressure and timing information during the act of signing. Dynamic signature verification is a replacement. 2.4 Face Recognition

To identify any person we generally look at face and eyes in particular seem to tell a story how the person feels.Face recognition is a kind of electronic unmasking 2.5 Palm Recognition The image of the hand is collected and the feature vectors are extracted and compared with the database feature vectors.

3.0

IRIS RECOGNITION SYSTEM

3.1 Example of iris recognition system

4.1 Iris Localization

4.0

TECHNIQUES USED

Both the inner boundary and the outer boundary of a typical iris can be taken as circles. But the two circles are usually not co-centric. Compared with the other part of the eye, the pupil is much darker. We detect the inner boundary between the pupil and the iris. The outer boundary of the iris is more difficult to detect because of the low contrast between the two sides of the boundary. We detect the outer boundary by maximizing changes of the perimeter- normalized along the circle. The technique is found to be efficient and effective. 4.2 Iris Normalization The size of the pupil may change due to the variation of the illumination and the associated elastic deformations in the iris texture may interface with the results of pattern matching. For the purpose of accurate texture analysis, it is necessary to compensate this deformation. Since both the inner and outer boundaries of the iris have been detected, it is easy to map the iris ring to a rectangular block of texture of a fixed size. 4.3 Image Enhancement The original image has low contrast and may have non-uniform illumination caused by the position of the light source. These may impair the result of the texture analysis. We enhance the iris image reduce the effect of non-uniform illumination.

5.0 WORKING OF IRIS SYSTEM
An iris-recognition algorithm first has to identify the approximately concentric circular outer boundaries of the iris and the pupil in a photo of an eye. The set of pixels covering only the iris is then transformed into a bit pattern that preserves the information that is essential for a statistically meaningful comparison between two iris images. The mathematical methods used resemble those of modern lossy compression algorithms for photographic images. In the case of Daugman's algorithms, a Gabor wavelet transform is used in order to extract the spatial frequency range that contains a good best signal-to-noise ratio considering the focus quality of available cameras. The result is a set of complex numbers that carry local amplitude and phase information for the iris image. In Daugman's algorithms, all amplitude information is discarded, and the resulting 2048 bits that represent an iris consist only of the complex sign bits of the Gabor-domain representation of the iris image. Discarding the amplitude information ensures that the template remains largely unaffected by changes in illumination and virtually negligibly by iris color, which contributes significantly to the long-term stability of the biometric template. To authenticate via identification (one-to-many template matching) or verification (one-to-one template matching), a template created by imaging the iris is compared to a stored value template in a database. If the Hamming distance is below the decision threshold, a positive identification has effectively been made. A practical problem of iris recognition is that the iris is usually partially covered by eyelids and eyelashes. In order to reduce the false-reject risk in such cases, additional algorithms are

needed to identify the locations of eyelids and eyelashes and to exclude the bits in the resulting code from the comparison operation.

6.0 ADVANTAGES
The iris of the eye has been described as the ideal part of the human body for biometric identification for several reasons:



It is an internal organ that is well protected against damage and wear by a highly transparent and sensitive membrane (the cornea). This distinguishes it from fingerprints, which can be difficult to recognize after years of certain types of manual labor.



The iris is mostly flat, and its geometric configuration is only controlled by two complementary muscles (the sphincter pupillae and dilator pupillae) that control the diameter of the pupil. This makes the iris shape far more predictable than, for instance, that of the face.



The iris has a fine texture that—like fingerprints—is determined randomly during embryonic gestation. Even genetically identical individuals have completely independent iris textures, whereas DNA (genetic "fingerprinting") is not unique for the about 0.2% of the human population who have a genetically identical twin.



An iris scan is similar to taking a photograph and can be performed from about 10 cm to a few meters away. There is no need for the person to be identified to touch any equipment that has recently been touched by a stranger, thereby eliminating an objection that has been raised in some cultures against fingerprint scanners, where a finger has to touch a surface, or retinal scanning, where the eye can be brought very close to a lens (like looking into a microscope lens).



Some argue that a focused digital photograph with an iris diameter of about 200 pixels contains much more long-term stable information than a fingerprint.



The originally commercially deployed iris-recognition algorithm, John Daugman's IrisCode, has an unprecedented false match rate (better than 10−11).



While there are some medical and surgical procedures that can affect the colour and overall shape of the iris, the fine texture remains remarkably stable over many decades. Some iris identifications have succeeded over a period of about 30 years.

7.0 DISADVANTAGES
• Iris scanning is a relatively new technology and is incompatible with the very substantial investment that the law enforcement and immigration authorities of some countries have already made into fingerprint recognition. • Iris recognition is very difficult to perform at a distance larger than a few meters and if the person to be identified is not cooperating by holding the head still and looking into the camera. However, several academic institutions and biometric vendors are developing products that claim to be able to identify subjects at distances of up to 10 meters ("standoff iris" or "iris at a distance"). • As with other photographic biometric technologies, iris recognition is susceptible to poor image quality, with associated failure to enroll rates. • As with other identification infrastructure (national residents databases, ID cards, etc.), civil rights activists have voiced concerns that iris-recognition technology might help governments to track individuals beyond their will.

8.0 SECURITY CONSIDERATIONS
As with most other biometric identification technology, a still not satisfactorily solved problem with iris recognition is the problem of live-tissue verification. The reliability of any biometric identification depends on ensuring that the signal acquired and compared has actually been recorded from a live body part of the person to be identified and is not a manufactured template. Many commercially available iris-recognition systems are easily fooled by presenting a high-quality photograph of a face instead of a real face, which makes such devices unsuitable for unsupervised applications, such as door access-control systems. The problem of live-tissue verification is less of a concern in supervised applications (e.g., immigration control), where a human operator supervises the process of taking the picture. Methods that have been suggested to provide some defence against the use of fake eyes and irises include:



Changing ambient lighting during the identification (switching on a bright lamp), such that the pupillary reflex can be verified and the iris image be recorded at several different pupil diameters • Analysing the 2D spatial frequency spectrum of the iris image for the peaks caused by the printer dither patterns found on commercially available fake-iris contact lenses • Analysing the temporal frequency spectrum of the image for the peaks caused by computer displays



Using spectral analysis instead of merely monochromatic cameras to distinguish iris tissue from other material • Observing the characteristic natural movement of an eyeball (measuring nystagmus, tracking eye while text is read, etc.) • Testing for retinal retroreflection (red-eye effect) • Testing for reflections from the eye's four optical surfaces (front and back of both cornea and lens) to verify their presence, position and shape • Using 3D imaging (e.g., stereo cameras) to verify the position and shape of the iris relative to other eye features

9.0 CONCLUSION
Biometric technology has great potentialThere are many biometric products around,regarding the different biometric technologies Shortcomings of biometric systems due to


• •

manufacturers ignorance of security concerns lack of quality control standardisation problems

Biometric technology is very promising.Manufacturers have to take security concerns serious

10.0 REFERENCE
1. “IRIS Recognition- Wikipedia” http://en.wikipedia.org/wiki/Iris_recognition downloaded on 25/10/09 2. “Iris Recognition Software” www.fulcrumbiometrics.com downloaded on 25/10/09 3.” Iris Recognition Homepage - Iris recognition and identification” www.iris-recognition.org downloaded on 25/10/09 4. “Iris Recognition System” Iris-Recognition-System/3000-2053_4-10553145.html downloaded on 25/10/09 5.” Iris Recognition” www.hrsltd.com/technology. downloaded on 26/10/09 6. “Iris Recognition” www.biometrics.gov/Documents/IrisRec.pdf downloaded on26/10/09

7. “IMAGE PROCESSING: Iris recognition system uses dual FireWire ..” www.visionsystems.com/.../IMAGE-PROCESSING:-Iris-recognition-system-uses-dual-FireWirecamera – downloaded on 26/10/09 8.”Iris Recognition System 1.0 - Iris Recognition System is” www.softpedia.com/get/.../Iris-Recognition-System.shtml downloaded on 26/10/09 9.” Open Source Iris Recognition Implementation” www.csse.uwa.edu.au/~pk/studentprojects/libor/ downloaded on26/10/09 10” EyeJudge Iris Recognition and Verification System” www.eyejudge.com downloaded on26/10/09 11.” iris Recognition” www.iris-recognition.org/downloaded on 26/10/09 12.” Iris Scanning Technology: Coming of Age” www.merinews.com/article/irisscanning.../128618.shtml downloaded on 26/10/09 13.” Iris recognition” www.cl.cam.ac.uk/~jgd1000/ downloaded on 26/10/09 14.” Article: Iridian Says Iris Recognition System Deployed in Middle ...” www.accessmylibrary.com/.../summary_0286-6553780_ITM downloaded on 27/10/09 15 “Eye Controls-iris recognition biometrics for clinical and medical ...” www.eyecontrols.com/ - downloaded on 27/10/09

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