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Displaying 1-4 out of 4 total
An Automatic Iris Occlusion Estimation Method Based on High-Dimensional Density Estimation
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Yung-Hui Li,M. Savvides
Issue Date:April 2013
pp. 784-796
Iris masks play an important role in iris recognition. They indicate which part of the iris texture map is useful and which part is occluded or contaminated by noisy image artifacts such as eyelashes, eyelids, eyeglasses frames, and specular reflections. T...
 
A pixel-wise, learning-based approach for occlusion estimation of iris images in polar domain
Found in: Acoustics, Speech, and Signal Processing, IEEE International Conference on
By Yung-hui Li, Marios Savvides
Issue Date:April 2009
pp. 1357-1360
On normalized iris images, there are many kinds of noises, such as eyelids, eyelashes, shadows or specular reflections, that often occlude the true iris texture. If high recognition rate is desired, those occluded areas must be estimated accurately in orde...
 
Investigating useful and distinguishing features around the eyelash region
Found in: Applied Image Pattern Recognition Workshop,
By Yung-hui Li, Marios Savvides, Tsuhan Chen
Issue Date:October 2008
pp. 1-6
Traditionally, iris recognition is always about analyzing and extracting features from iris texture. We proposed to investigate regions around eyelashes and extract useful information which helps us to perform ethnic classification. We propose an algorithm...
 
Kernel Fukunaga-Koontz Transform Subspaces For Enhanced Face Recognition
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Yung-hui Li, Marios Savvides
Issue Date:June 2007
pp. 1-8
Traditional linear Fukunaga-Koontz Transform (FKT) [1] is a powerful discriminative subspaces building approach. Previous work has successfully extended FKT to be able to deal with small-sample-size. In this paper, we extend traditional linear FKT to enabl...
 
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