Iris Segmentation
12 papers with code • 3 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Iris Segmentation
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CASIA-Iris-Complex
UBIRIS.v2
Most implemented papers
Reconstruction and Quantification of 3D Iris Surface for Angle-Closure Glaucoma Detection in Anterior Segment OCT
iMED-Lab/WRB-Net
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We consider it to be the first work to detect angle-closure glaucoma by means of 3D representation.
Open Source Iris Recognition Hardware and Software with Presentation Attack Detection
CVRL/RaspberryPiOpenSourceIris
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This paper proposes the first known to us open source hardware and software iris recognition system with presentation attack detection (PAD), which can be easily assembled for about 75 USD using Raspberry Pi board and a few peripherals.
Iris Recognition with Image Segmentation Employing Retrained Off-the-Shelf Deep Neural Networks
This paper offers three new, open-source, deep learning-based iris segmentation methods, and the methodology how to use irregular segmentation masks in a conventional Gabor-wavelet-based iris recognition.
Learning-Free Iris Segmentation Revisited: A First Step Toward Fast Volumetric Operation Over Video Samples
Subject matching performance in iris biometrics is contingent upon fast, high-quality iris segmentation.
Post-mortem Iris Recognition with Deep-Learning-based Image Segmentation
We propose to use deep learning-based iris segmentation models to extract highly irregular iris texture areas in post-mortem iris images.
Joint Iris Segmentation and Localization Using Deep Multi-task Learning Framework
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.
Gender Classification from Iris Texture Images Using a New Set of Binary Statistical Image Features
This paper explores the use of a Binary Statistical Features (BSIF) algorithm for classifying gender from iris texture images captured with NIR sensors.
A Resource-Efficient Embedded Iris Recognition System Using Fully Convolutional Networks
To attain accurate and efficient FCN models, we propose a three-step SW/HW co-design methodology consisting of FCN architectural exploration, precision quantization, and hardware acceleration.
Boltzmann Exploration Expectation–Maximisation
While effective, the success of any monotone algorithm is crucially dependant on good parameter initialisation, where a common choice is K-means initialisation, commonly employed for Gaussian mixture models.
Interpretable Deep Learning-Based Forensic Iris Segmentation and Recognition
In this paper, we present an end-to-end deep learning-based method for postmortem iris segmentation and recognition with a special visualization technique intended to support forensic human examiners in their efforts.
