Analysis of 2D log-Gabor Filters to Encode Iris Patterns

This paper presents an analysis of the parameters used to construct 2D log-Gabor filters to encode iris patterns. This filter is a band-pass complex filter composed by four parameters that are used to extract information direct in the 2D domain. An iris recognition system, composed by segmentation, normalization, encoding and matching is also described. The segmentation module combines the Pulling & Pushing and Active Contour Model and the Circular Hough Transform to find the inner and the outer boundaries of the iris. The experiments were performed using the CASIA v1 iris database and the results are analyzed using ROC curves. We conclude that 2D log-Gabor filters are also an effective alternative to encode the features present on iris patterns. The combination of the modified segmentation procedure and the use of 2D Log-Gabor filters showed good results for certain important regions of the ROC curves.