Iris Encoding and Recognition using Gabor Wavelets
The method of encoding iris patterns that is used in all current public deployments of iris recognition technology is based on a set of mathematical functions called Gabor wavelets that analyze and extract the unique texture of an iris. They encode it in terms of its phase structure at multiple scales of analysis. When this phase information is coarsely quantized, it creates a random bit stream that is sufficiently stable for a given eye, yet random and diverse for different eyes, that iris patterns can be recognized very rapidly and reliably over large databases by a simple test of statistical independence. The success of this biometric algorithm may be attributed in part to certain important properties of the Gabor wavelets as encoders, and to the simplicity and efficiency of searches for matches when pattern information is represented in terms of such phase bit strings.
Different biometric modalities use...
- 3.Meyer, Y.: Principe d’incertitude, bases hilbertiennes et algebres d’operateurs. Bourbaki Seminar 662 (1985)Google Scholar
- 5.Gabor, D.: Theory of communication. J. Inst. Electr. Eng. 93, 429–457 (1946)Google Scholar
- 7.Jones, J.P., Palmer, L.A.: An evaluation of the 2D Gabor filter model of simple receptive fields in cat striate cortex. J. Neurophysiol. 58, 1233–1258 (1987)Google Scholar
- 11.Newton, I.: Method of fluxions. Manuscript in Trinity College Library, University of Cambridge (1671)Google Scholar
- 15.Kong, A.W.K.: Palmprint Iientification based on generalization of irisCode. Ph.D. thesis, University of Waterloo, ON, Canada (2007)Google Scholar