Proceedings ArticleDOI
Revisiting iris recognition with color cosmetic contact lenses
Naman Kohli,Daksha Yadav,Mayank Vatsa,Richa Singh +3 more
- pp 1-7
Reads0
Chats0
TLDR
An in-depth analysis of the effect of contact lens on iris recognition performance is presented and the results computed using VeriEye suggest that color cosmetic lens significantly increases the false rejection at a fixed false acceptance rate.Abstract:
Over the years, iris recognition has gained importance in the biometrics applications and is being used in several large scale nationwide projects. Though iris patterns are unique, they may be affected by external factors such as illumination, camera-eye angle, and sensor interoperability. The presence of contact lens, particularly color cosmetic lens, may also pose a challenge to iris biometrics as it obfuscates the iris patterns and changes the inter and intra-class distributions. This paper presents an in-depth analysis of the effect of contact lens on iris recognition performance. We also present the IIIT-D Contact Lens Iris database with over 6500 images pertaining to 101 subjects. For each subject, images are captured without lens, transparent (prescription) lens, and color cosmetic lens (textured) using two different iris sensors. The results computed using VeriEye suggest that color cosmetic lens significantly increases the false rejection at a fixed false acceptance rate. Also, the experiments on four existing lens detection algorithms suggest that incorporating lens detection helps in maintaining the iris recognition performance. However further research is required to build sophisticated lens detection algorithm that can improve iris recognition.read more
Citations
More filters
Journal ArticleDOI
Cross-database and cross-attack Iris presentation attack detection using micro stripes analyses
Meiling Fang,Meiling Fang,Naser Damer,Naser Damer,Fadi Boutros,Fadi Boutros,Florian Kirchbuchner,Florian Kirchbuchner,Arjan Kuijper,Arjan Kuijper +9 more
TL;DR: An in-depth experimental evaluation of this framework reveals a superior performance in three databases compared with state-of-the-art (SoTA) algorithms and baselines, and minimizes the confusion between textured and transparent presentations in comparison to SoTA methods.
Journal ArticleDOI
Ocular recognition databases and competitions: a survey
TL;DR: A survey of the databases created for ocular recognition, detailing their protocols and how their images were acquired and some relevant works applying deep learning techniques to ocular Recognition point out new challenges and future directions.
Proceedings ArticleDOI
Deep Sparse Feature Selection and Fusion for Textured Contact Lens Detection
TL;DR: This approach builds upon existing hand-crafted image features and neural network architectures by optimally selecting and combining the most useful set of features into a single model and achieves roughly a four times increase in performance over the state-of-the-art on three benchmark textured lens datasets.
Journal ArticleDOI
Enhanced iris presentation attack detection via contraction-expansion CNN
TL;DR: Li et al. as mentioned in this paper proposed a two head contraction expansion convolutional neural network (CNN) architecture for robust presentation attack detection, which consists of raw image and edge enhanced image to learn discriminating features for binary classification.
Posted Content
UFPR-Periocular: A Periocular Dataset Collected by Mobile Devices in Unconstrained Scenarios.
Luiz A. Zanlorensi,Rayson Laroca,Diego R. Lucio,Lucas R. Santos,Alceu S. Britto,David Menotti +5 more
TL;DR: A new periocular dataset containing samples from 1,122 subjects, acquired in 3 sessions by 196 different mobile devices is presented, and an extensive benchmark with several Convolutional Neural Network architectures and models that have been employed in state-of-the-art approaches based on Multi-class Classification, Multitask Learning, Pairwise Filters Network, and Siamese Network is performed.
References
More filters
Journal ArticleDOI
Demodulation by complex-valued wavelets for stochastic pattern recognition
TL;DR: This paper discusses exploitation of this statistical principle, combined with wavelet image coding methods to extract phase descriptions of incoherent patterns from stochastic signals.
Journal ArticleDOI
Improving Iris Recognition Performance Using Segmentation, Quality Enhancement, Match Score Fusion, and Indexing
TL;DR: This paper proposes algorithms for iris segmentation, quality enhancement, match score fusion, and indexing to improve both the accuracy and the speed of iris recognition.
Proceedings ArticleDOI
Counterfeit iris detection based on texture analysis
TL;DR: This paper proposes three measures to detect fake iris: measuring iris edge sharpness, applying Iris-Texton feature for characterizing the visual primitives of iris textures and using selected features based on co-occurrence matrix (CM).
Journal ArticleDOI
Pupil dilation degrades iris biometric performance
TL;DR: It is found that when the degree of dilation is similar at enrollment and recognition, comparisons involving highly dilated pupils result in worse recognition performance than comparisons involving constricted pupils, and it is recommended that a measure of pupil dilation be kept as meta-data for every iris code.
Proceedings ArticleDOI
Contact Lens Detection Based on Weighted LBP
Hui Zhang,Zhenan Sun,Tieniu Tan +2 more
TL;DR: A novel fake iris detection algorithm based on improved LBP and statistical features is proposed, which achieves state-of-the-art performance in contact lens spoof detection.