Joint Iris Segmentation and Localization Using Deep Multi-task Learning Framework

by   Caiyong Wang, et al.

Iris segmentation and localization in non-cooperative environment is challenging due to illumination variations, long distances, moving subjects and limited user cooperation, etc. Traditional methods often suffer from poor performance when confronted with iris images captured in these conditions. Recent studies have shown that deep learning methods could achieve impressive performance on iris segmentation task. In addition, as iris is defined as an annular region between pupil and sclera, geometric constraints could be imposed to help locating the iris more accurately and improve the segmentation results. In this paper, we propose a deep multi-task learning framework, named as IrisParseNet, to exploit the inherent correlations between pupil, iris and sclera to boost up the performance of iris segmentation and localization in a unified model. In particular, IrisParseNet firstly applies a Fully Convolutional Encoder-Decoder Attention Network to simultaneously estimate pupil center, iris segmentation mask and iris inner/outer boundary. Then, an effective post-processing method is adopted for iris inner/outer circle localization.To train and evaluate the proposed method, we manually label three challenging iris datasets, namely CASIA-Iris-Distance, UBIRIS.v2, and MICHE-I, which cover various types of noises. Extensive experiments are conducted on these newly annotated datasets, and results show that our method outperforms state-of-the-art methods on various benchmarks. All the ground-truth annotations, annotation codes and evaluation protocols are publicly available at


page 1

page 2

page 3

page 5

page 6

page 7


Segmentation-free Direct Iris Localization Networks

This paper proposes an efficient iris localization method without using ...

Novel Deep Learning Framework For Bovine Iris Segmentation

Iris segmentation is the initial step to identify biometric of animals t...

A fast and accurate iris segmentation method using an LoG filter and its zero-crossings

This paper presents a hybrid approach to achieve iris localization based...

DeepIrisNet2: Learning Deep-IrisCodes from Scratch for Segmentation-Robust Visible Wavelength and Near Infrared Iris Recognition

We first, introduce a deep learning based framework named as DeepIrisNet...

D-NetPAD: An Explainable and Interpretable Iris Presentation Attack Detector

An iris recognition system is vulnerable to presentation attacks, or PAs...

Semantic Segmentation of Periocular Near-Infra-Red Eye Images Under Alcohol Effects

This paper proposes a new framework to detect, segment, and estimate the...

Please sign up or login with your details

Forgot password? Click here to reset