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Objectives: Iris recognition is one of biometric identification methods adopted over worldwide. In this paper we intend to update the previous survey and cover the survey over the period of roughly 2010 to 2015. Methods: We focus on the paper that appeared in Springer, IEEE Xplore and International Conferences, National and International journals covering Image Processing, Signal Processing, Pattern recognition and Bioinformatics. This paper primarily focuses on the survey of Iris camera for Iris acquisition, Methods adopted for iris segmentation, feature extraction, matching and public Iris database. Iris segmentation and feature extraction are important steps in Iris recognition. As there are several publications on the segmentation and feature extraction separately in literature, we have selected and summarized only prominent work in our paper. Findings: We have compared the algorithm used by various researchers with the performance parameter obtained by other researchers. We have found that there is scope for improvement in algorithms and need to understand the Iris Code in detail. Application: This comparative analysis will help researcher to get view on present scenario related to Iris recognition system.

Keywords

Acquisition Segmentation, Database, Features, Iris, Matching.
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