Hu et al., 2015 - Google Patents
Exploiting stable and discriminative iris weight map for iris recognition under less constrained environmentHu et al., 2015
- Document ID
- 10861898113207683759
- Author
- Hu Y
- Sirlantzis K
- Howells G
- Publication year
- Publication venue
- 2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS)
External Links
Snippet
In this paper, we address the problem of iris recognition under less constrained environment. We propose a novel iris weight map for iris matching stage to improve the robustness of iris recognition to the noise and degradations in less constrained environment …
- 210000000554 Iris 0 title abstract description 144
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Soleymani et al. | Multi-level feature abstraction from convolutional neural networks for multimodal biometric identification | |
Kumar Jindal et al. | Face template protection using deep convolutional neural network | |
Umer et al. | A novel cancelable iris recognition system based on feature learning techniques | |
Alonso‐Fernandez et al. | Near‐infrared and visible‐light periocular recognition with Gabor features using frequency‐adaptive automatic eye detection | |
Nguyen et al. | Complex-valued iris recognition network | |
Malhotra et al. | Fingerphoto authentication using smartphone camera captured under varying environmental conditions | |
Ramesha et al. | Face recognition system using discrete wavelet transform and fast PCA | |
Jindal et al. | Securing face templates using deep convolutional neural network and random projection | |
Bala et al. | Multimodal biometric system based on fusion techniques: a review | |
Aravinth et al. | Multi classifier-based score level fusion of multi-modal biometric recognition and its application to remote biometrics authentication | |
Hu et al. | Exploiting stable and discriminative iris weight map for iris recognition under less constrained environment | |
González‐Soler et al. | On the generalisation capabilities of Fisher vector‐based face presentation attack detection | |
Singh et al. | A generic framework for deep incremental cancelable template generation | |
Raveendra et al. | Performance evaluation of face recognition system by concatenation of spatial and transformation domain features | |
Prasad et al. | Face recognition using PCA and feed forward neural networks | |
Hu et al. | A novel iris weight map method for less constrained iris recognition based on bit stability and discriminability | |
Dhiman et al. | An introduction to deep learning applications in biometric recognition | |
Hu et al. | Signal-level information fusion for less constrained iris recognition using sparse-error low rank matrix factorization | |
Kong | IrisCode decompression based on the dependence between its bit pairs | |
Gangwar et al. | Robust periocular biometrics based on local phase quantisation and gabor transform | |
Jagadeesh et al. | DBC based Face Recognition using DWT | |
Luo et al. | A robust single-sensor face and iris biometric identification system based on multimodal feature extraction network | |
Verma et al. | Fuzzy brain storm optimization and adaptive thresholding for multimodal vein-based recognition system | |
Kim et al. | A performance driven methodology for cancelable face templates generation | |
Chan et al. | A further study of low resolution androgenic hair patterns as a soft biometric trait |