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An Efficient Algorithm for Iris Pattern

Published on Jan 21, 2016


Wavelet analysis have received significant attention because their multi-resolution decomposition allows efficient image analysis. It is widely used for varied applications such as noise reduction, and data compression, etc. In this paper we have introduced and applied the concept of 2 dimensional Gabor wavelet transform to Biometric Iris recognition system.

The application of this transform in encoding the iris image for pattern recognition proves to achieve increased accuracy and processing speed compared to other methods. With a strong scientific approach and mathematical background we have developed an algorithm to facilitate the implementation of this method under the platforms of MATLAB

IMAGES - An introduction:

A dictionary defines image as a "reproduction or representation of the form of a person or thing". The inherent association of a human with the visual senses, predisposes one to conceive an image as a stimulus on the retina of the eye, in which case the mechanism of optics govern the image formation resulting in continuos range, multi-tone images.

A digital image can be defined to be a numerical representation of an object or more strictly to be sampled, quantized function of two dimensions which has been generated by optical means, sampled in an equally spaced rectangular grid pattern, and quantized in equal intervals of graylevel.

The word is crying out for the simpler access controls to personal authentication systems and it looks like biometrics may be the answer. Instead of carrying bunch of keys, all those access cards or passwords you carry around with you, your body can be used to uniquely identify you. Furthermore, when biometrics measures are applied in combination with other controls, such as access cards or passwords, the reliability of authentication controls takes a giant step forward.


Biometrics is best defined as measurable physiological and/or behavioral characteristics that can be utilized to verify the identity of an indivisual. They include the following:

" Iris scanning

" Facial recognition

" Fingerprint verification

" Hand geometry

" Retinal scanning

" Signature verification

" Voice verification


" Highly protected internal organ of the eye.

" Iris patterns possess a high degree of randomness.

" Variability: 244 degrees of freedom.

" Entropy: 3.2 bits per square millimetre.

" Uniqueness: set by combinatorial complexity.

" Patterns apparently stable throughout life.

IRIS - An introduction:

The iris is a colored ring that surrounds the pupil and contains easily visible yet complex and distinct combinations of corona, pits, filaments, crypts, striations, radial furrows and more.

The iris is called the "Living password" because of its unique, random features. It's always with you and can't be stolen or faked. As such it makes an excellent biometrics identifier.

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