JOURNAL ARTICLE

Encoder-Decoder Convolutional Neural Network Based Iris-Sclera Segmentation

Abstract

Iris-sclera biometry is one of the features that yields high accuracy in user recognition and liveness detection systems. In this study, segmentation processes the first stage of an iris-sclera user verification system have been considered. Traditional and convolutional neural network based deep learning methods have been used for iris-sclera segmentation. Performance of the investigated methods has been tested on two distinct eye image datasets (UBIRIS and self-collected data). Our experimental results show that deep learning based segmentation methods outperformed conventional methods in terms of dice score on both datasets.

Keywords:
Sclera Computer science Segmentation Artificial intelligence IRIS (biosensor) Deep learning Convolutional neural network Image segmentation Liveness Iris recognition Computer vision Encoder Pattern recognition (psychology) Artificial neural network Biometrics

Metrics

4
Cited By
0.49
FWCI (Field Weighted Citation Impact)
4
Refs
0.63
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Biometric Identification and Security
Physical Sciences →  Computer Science →  Signal Processing
User Authentication and Security Systems
Physical Sciences →  Computer Science →  Information Systems

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