Proceedings ArticleDOI
Revisiting iris recognition with color cosmetic contact lenses
Naman Kohli,Daksha Yadav,Mayank Vatsa,Richa Singh +3 more
- pp 1-7
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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
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Proceedings ArticleDOI
Synthesizing Iris Images Using RaSGAN With Application in Presentation Attack Detection
TL;DR: A new technique for generating synthetic iris images is designed and its potential for presentation attack detection (PAD) is demonstrated and the viability of using these synthetic images to train a PAD system that can generalize well to "unseen" attacks is demonstrated.
Face anti-spoofing via motion magnification and multifeature videolet aggregation
TL;DR: A new framework for face spoofing detection in videos using motion magnification and multifeature evidence aggregation in a windowed fashion is presented, which yields state-of-the-art performance and robust generalizability with low computational complexity.
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Using iris and sclera for detection and classification of contact lenses
TL;DR: A machine-learning approach for this task, based on expressive local image descriptors, shows that the proposed classification method based on a dense scale invariant descriptor outperforms all the reference techniques.
Proceedings ArticleDOI
Synthetic iris presentation attack using iDCGAN
TL;DR: In this paper, a novel iris presentation attack using deep learning based synthetic iris generation is presented. But, the attack is limited to textured contact lenses and print attacks.
Proceedings ArticleDOI
Detecting Textured Contact Lens in Uncontrolled Environment Using DensePAD
TL;DR: A new Unconstrained Multi-sensor Iris Presentation Attack (UnMIPA) database is created and a novel algorithm, DensePAD, which utilizes DenseNet based convolutional neural network architecture for iris presentation attack detection is presented.
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Proceedings ArticleDOI
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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.