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
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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.