Local feature extraction for iris recognition with automatic scale selection

This paper presents an iris recognition system using automatic scale selection algorithm for iris feature extraction. The proposed system first filters the given iris image adopting a bank of Laplacian of Gaussian (LoG) filters with many different scales and computes the normalized response of every filter. The parameter γ used to normalize the filter responses, is derived by analyzing the scale-space maxima of the blob feature detector responses. Then the maxima normalized response over scales for each point are selected together as the optimal filter outputs of the given iris image and the binary codes for iris feature representation are achieved by encoding these optimal outputs through a zero threshold. Comparison experiment results clearly demonstrate an efficient performance of the proposed algorithm.