In todayâ„¢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. ID cards can be almost lost, forged or misplaced: passwords can be forgotten. Biometric technology has now become a viable alternative to traditional identification systems because of its tremendous accuracy and speed. This paper explores the concept of Iris recognition which is one of the most popular biometric techniques. This technology finds applications in diverse fields.
IRIS SCAN AND BIOMETRICS
Bio Medical | Electronics Seminar Topic
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.
in need of seminars report on iris recognition
to get information about the topic Iris Scan full report ppt and related topic refer the link bellow