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ABSTRACT
A method for rapid visual recognition of personal identity is described, based on the failure of statistical test of independence. The most unique phenotypic feature visible in a person?s face is the detailed texture of each eye?s iris: an estimate of its statistical complexity in a sample of the human population reveals variation corresponding to several hundred independent degrees-of-freedom. Morphogenetic randomness in the texture expressed phenotypically in the iris trabeclar meshwork ensures that a test of statistical independence on two coded patterns organizing from different eyes is passed almost certainly, whereas the same test is failed almost certainly when the compared codes originate from the same eye. The visible texture of a person?s iris in a real time video image is encoded into a compact sequence of multi-scale quadrature 2-D Gabor wavelet coefficients, whose most significant bits comprise a 512 ? byte ?IRIS?CODE? statistical decision theory generates identification decisions from Exclusive-OR comparisons of complete iris code at the rate of 4,000 per second, including calculation of decision confidence levels. The distributions observed empirically in such comparisons imply a theoretical ?cross-over? error rate of one in 1,31,000 when a decision criterion is adopted that would equalize the False Accept and False Reject error rates.
INTRODUCTION
Reliable automatic recognition of persons has long been an attractive goal. As in all pattern recognition problems, the key issue is the relation between interclass and intra-class variability: objects can be reliably classified only if the variability among different instances of a given class is less than the variability between different classes. Iris patterns become interesting as an alternative approach to reliable visual recognition of persons when imaging can be done at distances of less than a meter, and especially when there is a need to search very large databases without incurring any false matches despite a huge number of possibilities. The iris has the great mathematical advantage that its pattern variability among different persons is enormous. In addition, as an internal (yet externally visible) organ of the eye, the iris is well protected from the environment and stable over time. As a planar object its image is relatively insensitive to angle of illumination, and changes in viewing angle cause only affine transformations; even the non-affine pattern distortion caused by pupillary dilation is readily reversible. Finally, the ease of localizing eyes in faces, and the distinctive annular shape of the iris, facilitates reliable and precise isolation of this feature and the creation of a size-invariant representation.
Algorithms developed by Dr. John Daugman at Cambridge are today the basis for all iris recognition systems worldwide
IRIS SCAN AND BIOMETRICS
Biometrics, the use of a physiological or behavioral aspect of the human body for authentication or identification, is a rapidly growing industry . Biometric solutions are used successfully in fields as varied as e-commerce, network access, time and attendance, ATM?s, corrections, banking, and medical record access. Biometrics? ease of use, accuracy, reliability, and flexibility are quickly establishing them as the premier authentication technology.Efforts to devise reliable mechanical means for biometric personal identification have a long and colourful history. In the Victorian era for example, inspired by birth of criminology and a desire to identify prisoners and malefactors, Sir Francis Galton F.R.S proposed various biometric indices for facial profiles which he represented numerically. Seeking to improve on the system of French physician Alphonse Bertillon for classifying convicts into one of 81 categories, Galton devised.
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IRIS SCAN
A method for rapid visual recognition of personal identity is described, based on the failure of statistical test of independence. The most unique phenotypic feature visible in a person s face is the detailed texture of each eye s iris: an estimate of its statistical complexity in a sample of the human population reveals variation corresponding to several hundred independent degrees-of-freedom. Morphogenetic randomness in the texture expressed phenotypically in the iris trabeclar meshwork ensures that a test of statistical independence on two coded patterns organizing from different eyes is passed almost certainly, whereas the same test is failed almost certainly when the compared codes originate from the same eye. The visible texture of a person s iris in a real time video image is encoded into a compact sequence of multi-scale quadrature 2-D Gabor wavelet coefficients, whose most significant bits comprise a 512 byte IRIS CODE statistical decision theory generates identification decisions from Exclusive-OR comparisons of complete iris code at the rate of 4,000 per second, including calculation of decision confidence levels. The distributions observed empirically in such comparisons imply a theoretical cross-over error rate of one in 1,31,000 when a decision criterion is adopted that would equalize the False Accept and False Reject error rates.
Reliable automatic recognition of persons has long been an attractive goal. As in all pattern recognition problems, the key issue is the relation between interclass and intra-class variability: objects can be reliably classified only if the variability among different instances of a given class is less than the variability between different classes. Iris patterns become interesting as an alternative approach to reliable visual recognition of persons when imaging can be done at distances of less than a meter, and especially when there is a need to search very large databases without incurring any false matches despite a huge number of possibilities. The iris has the great mathematical advantage that its pattern variability among different persons is enormous. In addition, as an internal (yet externally visible) organ of the eye, the iris is well protected from the environment and stable over time. As a planar object its image is relatively insensitive to angle of illumination, and changes in viewing angle cause only affine transformations; even the non-affine pattern distortion caused by pupillary dilation is readily reversible. Finally, the ease of localizing eyes in faces, and the distinctive annular shape of the iris, facilitates reliable and precise isolation of this feature and the creation of a size-invariant representation.
Algorithms developed by Dr. John Daugman at Cambridge are today the basis for all iris recognition systems worldwide
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Biometrics is an automated method of capturing a person s unique biological data that distinguishes him or her from another individual. Iris recognition has emerged as one of the most powerful and accurate identification techniques in the modern world. It has proven to be most fool proof technique for the identification of individuals with out the use of cards. PIN s and passwords. It facilitates automatic identification where by electronic transactions or access to places, information or accounts are made easier, quicker and more secure. The technical performance capability of the iris recognition process far surpasses that of any biometric technology now available. Iridian process is defined for rapid exhaustive search for very large databases: distinctive capability required for authentication today. The extremely low probabilities of getting a false match enable the iris recognition algorithms to search through extremely large databases, even of a national or planetary scale. As iris technology grows less expensive, it could very likely unseat a large portion of the biometric industry, e-commerce included; its technological superiority has already allowed it to make significant inroads into identification and security venues which had been dominated by other biometrics. Iris-based biometric technology has always been an exceptionally accurate one, and it may soon grow much more prominent.
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Biometrics is an automated method of capturing a person?s unique biological data that distinguishes him or her from another individual. Iris recognition has emerged as one of the most powerful and accurate identification techniques in the modern world. It has proven to be most fool proof technique for the identification of individuals with out the use of cards. PIN?s and passwords. It facilitates automatic identification where by electronic transactions or access to places, information or accounts are made easier, quicker and more secure. The technical performance capability of the iris recognition process far surpasses that of any biometric technology now available. Iridian process is defined for rapid exhaustive search for very large databases: distinctive capability required for authentication today. The extremely low probabilities of getting a false match enable the iris recognition algorithms to search through extremely large databases, even of a national or planetary scale. As iris technology grows less expensive, it could very likely unseat a large portion of the biometric industry, e-commerce included; its technological superiority has already allowed it to make significant inroads into identification and security venues which had been dominated by other biometrics. Iris-based biometric technology has always been an exceptionally accurate one, and it may soon grow much more prominent.
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plz sir can u plz send this topic
my mail:gorantla.ranjith@gmail.com
