This article presents an application of wavelet packet analysis to the features extraction part of an iris recognition system. An energy measure is used to identify the particular packets that carries discriminating information about the iris texture. Several different orthogonal wavelets are tested and a comparison to nonorthogonal analysis using Gabor wavelets is done. The experimental results show 100% correct classifications when applying the algorithm on an iris image database and the new algorithm is therefore an interesting alternative to Gabor based methods.

This paper presents an iris recognition system, based on a wavelet packet analysis using orthogonal wavelets. The identification of the different packets that carry discriminating information about the iris texture is carried out through an energy measure. Tests, conducted on a database of 149 high quality iris images show good robustness in relation to changes in illumination, blurring, optical axis deviation or local defects in the images.

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This article presents a new eyelid localization algorithm based on a parabolic curve fitting. To deal with eyelashes, low contrast or false detection due to iris texture, we propose a two steps algorithm. First, possible edge candidates are selected by applying an edge detection on a restricted area inside the iris. Then, a gradient maximisation is applied along every parabola, on a larger area, to refine the parameters and select the best one. Experiments have been conducted on the CASIA-IrisV3-Interval database that have been manually segmented. A new performance measure is proposed, carried out by comparing the segmented images obtained by the proposed method with the manual segmentation.