Iris verification using correlation filters

Abstract

Iris patterns are believed to be an important class of biometrics suitable for subject verification and identification applications. Earlier methods proposed for iris recognition were based on generating iris codes from features generated by applying Gabor wavelet processing to iris images. Another approach to image recognition is the use of correlation filters. Correlation filter methods differ from many image-based recognition approaches in that two-dimensional Fourier transforms of the images are used in this approach. In correlation filter methods, normal variations in an authentic iris image can be accommodated by designing a frequency-domain array (called a correlation filter) that captures the consistent part of iris images while deemphasizing the varying parts. Correlation filters also offer other benefits such as shift-invariance, graceful degradation and closed-form solutions. In this paper, we discuss the basics of correlation filters and show how they can be used for iris verification. © Springer-Verlag 2003.