Consensual iris segmentation fusion

Abstract

Recent works have shown that fusion at segmentation level has contributed to the robustness in iris recognition compared with the one obtained from a single segmentation, due to different segmentation algorithms can produce different segmentations of a same eye image. Nevertheless, the fusion process may consider mistakes as important information and include it in the resulting merged image since the analysis in these methods is made pixel to pixel and the spatial relationships between pixel structures are not taken into account. In this paper, the idea of the consensus segmentation as a new method of segmentation fusion that ensure the spatial relationships between pixel structures is introduced. This proposal is based in the philosophy of the clustering ensemble algorithms, treating the iris segmentations as a set of superpixels. The experimental results on a benchmark database (UBIRIS v1) show promising results.