Iris Recognition Methods - Survey

Abstract

The premise is that a biometric is a measurable physical characteristic which are reliable than passwords. Iris biometry is used to recognize an individual in a natural and intuitive way. Secure communications and mobile commerce are some of the application areas. Iris based security applications thrive on infrared cameras and video cameras for logins and transaction authentications. Accuracy, algorithm speed and template size are attributes that are important for large-scale identity programs and national database applications. In this paper, different iris recognition methods which aid an appropriate outlook for future work to build integrated classifier on latest input devices for excellent business transactions are discussed. Benchmark databases, products are also discussed. Since the area is currently one of the most on the go and the bulk of research is very large, this survey covers some of the significant methods.

Some Observations from the Scrutiny of Different Methods used for Iris Recognition

“…[14] Daugman devised a test of statistical independence between two iris codes [8] and this has been implemented by many other authors including Masek [9] and Monro [10]. The Hamming Distance (HD) between the two irides to be compared is calculated.…”

Evaluation of Iris Recognition System on Multiple Feature Extraction Algorithms and its Combinations

“…This work suggests that human examination of pairs of iris images for forensic purposes may be feasible and results of experiments suggest that development of different approaches to automated iris image analysis could be used to improve current iris biometric technology. Vijaya et al [4] states that generally algorithm is divided into four steps, such as. localization, Normalization, Feature Extraction and Matching.…”

“…Moreover, being an internal organ of the eye, behind the cornea and the aqueous humor; it is almost impossible to surgically modify the iris without unacceptable risk of damage. Also, its physiological response to light provides a natural test against fake irises [11].…”

DWT and DCT based Robust Iris Feature Extraction and Recognition Algorithm for Biometric Personal Identification

“…Also changing iris pattern of any person without surgery with high risk is impossible. Thus it is considered as one of the most reliable biometric in case of biometrics-based identification/recognition systems [2,6].…”

“…The features are encoded to a format suitable for recognition. The fourth module, recognition achieves result by comparison of features with stored patterns [6,11].…”