07-01-2014, 12:49 PM
A TECHNICAL SEMINAR REPORT ON AN EFFICIENT ALGORITHM FOR IRIS PATTERN RECOGNITION
AN EFFICIENT ALGORITHM.doc (Size: 913.07 KB / Downloads: 35)
ABSTRACT:
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.
This study presents a new algorithm for biometric-based iris recognition system. The proposed iris identification algorithm consists of four major fundamental steps: image processing; image localization; IER extraction; and image pattern recognition. An image of an individual’s eye is processed into an 8-bit gray scale BMP image until the boundaries of the iris are detected. The IER (Iris Effective Region) feature is then extracted using the feature extraction algorithm. This IER feature is a 12x8 BMP image pattern which contains the gray values of the iris and will be used for pattern matching. The IER feature extracted is then used as input for the pattern recognition algorithm wherein the linear correlation coefficients are analyzed and will be used as the basis for the identification and verification of an individual.
WHY BIOMETRICS?
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.
IMAGES
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 gray level.
IRIS
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.
VISIBLE WAVELENGTH (VW) VS NEAR INFRARED (NIR) IMAGING
Most iris recognition systems acquire images of the iris in the visible wavelength (400-700 nm) or near infrared range (700 - 900 nm) of the electromagnetic spectrum. Each wavelength distinguishes different features of the iris with NIR and VW obtaining Information from the iris by its texture and pigmentation, respectively. The majority of iris recognition systems operate within the longer NIR spectrum which can penetrate dark-Coloured irides, the dominant phenotype of the human population, revealing texture not easily observed in the VW spectrum. The NIR spectrum also reduces iris pattern contamination by blocking ambient corneal reflections.
Although reducing reflections through NIR makes system recognitions robust, NIR imaging cannot distinguish the effects of melanin, the primary coloring component in irides. The melanin, also known as chromophore, mainly consists of two distinct heterogeneous macromolecules, called eumelanin (brown–black) and pheomelanin (yellow–reddish), whose absorbance at longer wavelengths in the NIR spectrum is negligible. At shorter wavelengths within the VW spectrum, however, these chromophores are excited and provide rich sources of information mainly coded as shape patterns in iris. Hosseini, et al. provide a comparison between these two imaging modalities and fused the results to boost the recognition rate.