Secure and Robust Iris Recognition Using Random Projections and Sparse Representations
By Jaishanker K. Pillai, Vishal M. Patel, Ramalingam Chellappa, Nalini K. Ratha. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011
333 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Information Systems, Signal Processing
View Paper: https://www.semanticscholar.org/paper/4b88d62d546732454bb80e500f591c0e9a385749
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Vishal M. Patel
- He Zhang
- Ramalingam Chellappa
- Ramachandra Raghavendra
- Christoph Busch
- Nalini K. Ratha
- Ming-Hsuan Yang
- Dacheng Tao
In Information Systems
- Vishal M. Patel
- Ramachandra Raghavendra
- Christoph Busch
- He Zhang
- Ramalingam Chellappa
- Nalini K. Ratha
- Anil K. Jain
In Signal Processing
- Vishal M. Patel
- Ramalingam Chellappa
- Ramachandra Raghavendra
- Christoph Busch
- He Zhang
- Nalini K. Ratha
- Song Wang
- Carlos Domingo Castillo
Citations in the corpus
- Person Identification Using Full-Body Motion and Anthropometric Biometrics from Kinect Videos (2012, background): “For example, high impact research has been conducted that identify people with similar facial, fingerprint, or iris biometrics [1–6] in 2D images or videos.”
- Sparse Representation-Based Open Set Recognition (2017, methodology): “matic target recognition in [4] and [5], respectively.”
- Robust Scheme for Iris Presentation Attack Detection Using Multiscale Binarized Statistical Image Features (2015, methodology): “In this work, we adopt the well-established baseline iris recognition system based on Gabor transform and Sparse Representation Classifier (SRC) [33].”
- Cancelable Biometrics: A review (2015, methodology): “In these methods, a function that is dependent on some parameter is used to generate protected biometric templates.”