computer-vision-8

Iris Recognition

3260 papers • 126 benchmarks • 313 datasets

This task has no description! Would you like to contribute one?

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in iris-recognition-17

Trend

Dataset

Best Model

Actions

No benchmarks available.

Libraries

i

Use these libraries to find iris-recognition-17 models and implementations

Developer-Y/cs-video-courses

2 papers 64,671

Datasets

Subtasks

Pupil Dilation

Most implemented papers

Domain-Specific Human-Inspired Binarized Statistical Image Features for Iris Recognition

K. Bowyer, A. Czajka, P. Flynn, Daniel Moreira•Thu Jul 12 2018

The new iris-domain-specific BSIF filters, the patches used in filter training, the database used in testing and the source codes of the designed iris recognition method are made available along with this paper to facilitate applications of this concept.

47

Content

0

Paper Graph

Open Source Presentation Attack Detection Baseline for Iris Recognition

K. Bowyer, A. Czajka, J. McGrath•Tue Sep 25 2018

This paper proposes the first, known to us, open source presentation attack detection (PAD) solution to distinguish between authentic iris images (possibly wearing clear contact lenses) and irises with textured contact lenses.

18 0

Paper Graph

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

Renu Sharma, A. Ross•Wed Jul 01 2020

This work proposes an effective and robust iris PA detector called D-NetPAD based on the DenseNet convolutional neural network architecture that demonstrates generalizability across PA artifacts, sensors and datasets.

55 0

Paper Graph

Analyzing Covariate Influence on Gender and Race Prediction From Near-Infrared Ocular Images

A. Ross, Denton Bobeldyk•Thu May 03 2018

It is demonstrated that it is possible to use simple texture descriptors, such as binarized statistical image feature and local binary patterns, to extract gender and race attributes from a near-infrared ocular image used in a typical iris recognition system.

6 0

Paper Graph

Open Source Iris Recognition Hardware and Software with Presentation Attack Detection

A. Czajka, Zhaoyuan Fang•Tue Aug 18 2020

A lightweight image complexity-guided convolutional network for fast and accurate iris segmentation, domain-specific human-inspired Binarized Statistical Image Features (BSIF) to build an iris template, and to combine 2D and 3D features for PAD are proposed.

18 0

Paper Graph

Ensemble of Multi-View Learning Classifiers for Cross-Domain Iris Presentation Attack Detection

A. Rocha, K. Bowyer, A. Czajka, Andrey Kuehlkamp, A. Pinto•Sat Nov 24 2018

This paper presents a new approach in iris presentation attack detection (PAD) by exploring combinations of convolutional neural networks (CNNs) and transformed input spaces through binarized statistical image features (BSIFs).

61 0

Paper Graph

Iris Recognition with Image Segmentation Employing Retrained Off-the-Shelf Deep Neural Networks

K. Bowyer, A. Czajka, Mateusz Trokielewicz, Daniel Kerrigan•Thu Jan 03 2019

In database-disjoint training and testing, it is shown that deep learning-based segmentation outperforms the conventional (OSIRIS) segmentation in terms of Intersection over Union calculated between the obtained results and manually annotated ground-truth.

33 0

Paper Graph

Post-mortem Iris Recognition with Deep-Learning-based Image Segmentation

A. Czajka, Mateusz Trokielewicz, P. Maciejewicz•Sun Jan 06 2019

This paper proposes to use deep learning-based iris segmentation models to extract highly irregular iris texture areas in post-mortem iris images, and shows how to use segmentation masks predicted by neural networks in conventional, Gabor- based iris recognition method, which employs circular approximations of the pupillary and limbic iris boundaries.

83 0

Paper Graph

Gender Classification from Iris Texture Images Using a New Set of Binary Statistical Image Features

Juan E. Tapia, Claudia Arellano•Tue Apr 30 2019

This paper explores the use of a Binary Statistical Features (BSIF) algorithm for classifying gender from iris texture images captured with NIR sensors and results are competitive with the state of the art in gender classification.

12 0

Paper Graph

ThirdEye: Triplet Based Iris Recognition without Normalization

Sohaib Ahmad, Benjamin Fuller•Fri Jul 12 2019

A new iris recognition system called ThirdEye is developed based on triplet convolutional neural networks that directly uses segmented images without normalization, suggesting that normalization is more important for less constrained environments.

26 0

Paper Graph

Adding a benchmark result helps the community track progress.