IRIS RECOGNITION BASED ON EMPIRICAL MODE DECOMPOSITION
IRIS RECOGNITION BASED ON EMPIRICAL MODE DECOMPOSITION
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Biometrics is automated methods of recognizing a person based on a physiological or behavioral characteristic. Among the features measured are face, fingerprints, hand geometry, handwriting, iris, retinal, vein, and voice. Biometric technologies are becoming the foundation of an extensive array of highly secure identification and personal verification solutions. As the level of security breaches and transaction fraud increases, the need for highly secure identification and personal verification technologies is becoming apparent.
There are two types of Biometric methods. One is called behavioral biometrics. It is used for verification purposes. Verification is determining if a person is who they say they are. This type of biometrics looks at patterns of how certain activities are performed by an individual.
Physical biometrics is the other type used for identification or verification purposes. This method is commonly used in criminal investigations. The behavioral biometrics are speech recognition, signature recognition, typing recognition. And similarly for physical biometrics fingerprint recognition, face recognition, iris recognition, ear recognition, DNA recognition, etc.
Out of all biometrics, iris recognition technique is a flexible, most reliable and accurate method for identification process due to its non-invasiveness. Iris pattern remains stable throughout the human life; it has complex structures and has no genetic penetrance. The possibility that the iris of the eye might be used as a kind of optical fingerprint for personal identification was suggested originally by the ophthalmologists, who noted from clinical experience that every iris has a highly detailed and unique structure, which remained unchanged in clinical photographs spanning decades. Most of biometric will have few distinct characteristics, but the iris is said to have hundreds of unique spots for recognition.
The human iris structure is shown in the Figure. The human iris is an annular part between the pupil and the white sclera. The iris begins to form in the third month of gestation. The formation of iris pattern is completed by the eighth month. Its complex pattern contains many distinctive features such as arching ligaments, furrows, ridges, crypts, rings, corona, and freckles. These features are extracted and used for recognition or verification. Iris color is determined by the density of melanin pigment in its anterior layer and stroma and its absence results in formation of blue irises. While matching process, the performance is much influenced by many parameters such as spatial position, orientation, center frequencies and size parameters filter kernel.
Iris recognition means analyzing the colored ring that surrounds the pupil and the patterns in this ring can be used for human identification. The iris recognition systems offer more reliability and accuracy compared to traditional personal identification methods such as ID cards and passwords, which can be easily stolen, lost, or forgotten.
USING EMPIRICAL MODE DECOMPOSITION FOR IRIS RECOGNITION
Empirical Mode Decomposition (EMD) is a multi resolution decomposition technique, which is adaptive and appears to be suitable for non-linear and non-stationary signal processing. The EMD method was originally proposed for the study of ocean waves , and found potential applications in geophysical exploration, underwater acoustic signals, noise removal filter and biomedicine etc. The major advantage of EMD is that the basis functions can be directly derived from the signal itself. Compared with Fourier analysis, EMD analysis is adaptive while the basis functions of Fourier analysis are linear combinations of fixed sinusoids. The principle of EMD is to decompose a signal into a sum of oscillatory functions, namely intrinsic mode functions (IMFs), that:
1) Have the same numbers of extrema and zero-crossings or differ at most by one.
2) are symmetric with respect to local zero mean. The above two conditions fulfill the physically necessary conditions to define a meaningful instantaneous frequency.
Advantage of Iris Recognition:
It is an internal organ that is well protected against damage and wear by a highly transparent and sensitive membrane. 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 that control the diameter of the pupil. This makes the iris shape far more predictable than, for instance, that of the face.
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.
Limitations of Iris Recognition:
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.
As with other photographic biometric technologies, iris recognition is susceptible to poor image quality, with increase in failure rate.
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.
Economically concern the Iris recognition is more expensive.