A hybrid method for accurate iris segmentation on at-a-distance visible-wavelength images

Félix Fuentes-Hurtado,Jose Antonio Diego-Mas,Mariano Alcañiz,Valery Naranjo

doi:10.1186/s13640-019-0473-0

Félix Fuentes-Hurtado, Jose Antonio Diego-Mas + Show 2 more

Open Access

https://doi.org/10.1186/s13640-019-0473-0

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Abstract

This work describes a new hybrid method for accurate iris segmentation from full-face images independently of the ethnicity of the subject. It is based on a combination of three methods: facial key-point detection, integro-differential operator (IDO) and mathematical morphology. First, facial landmarks are extracted by means of the Chehra algorithm in order to obtain the eye location. Then, the IDO is applied to the extracted sub-image containing only the eye in order to locate the iris. Once the iris is located, a series of mathematical morphological operations is performed in order to accurately segment it. Results are obtained and compared among four different ethnicities (Asian, Black, Latino and White) as well as with two other iris segmentation algorithms. In addition, robustness against rotation, blurring and noise is also assessed. Our method obtains state-of-the-art performance and shows itself robust with small amounts of blur, noise and/or rotation. Furthermore, it is fast, accurate, and its code is publicly available.

Highlights

Iris offers high accuracy for individual identification as it is unique to each person and remains unchanged during its entire lifetime
1.2 Our work In this work, we present a full framework for iris segmentation that works with full-face photographs as input
5 Results and discussion As mentioned previously, the proposed iris segmentation framework is tested in a database consisting of real face photographs of male and female subjects from four different ethnicities, namely Asian, Black, Latino and White

Summary

Introduction

Iris offers high accuracy for individual identification as it is unique to each person and remains unchanged during its entire lifetime. Iris recognition has been under research during the last decade in order to find the most accurate and robust algorithm as possible. It can be used in applications related to personal identification such as secure access to bank accounts at automatic teller machines, to buildings, national border controls, passport control, etc. Iris can be used for gender estimation or ethnicity detection [2,3,4,5].

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