Title
Eye detection by complex filtering for periocular recognition
Abstract
We present a novel system to localize the eye position based on symmetry filters. By using a 2D separable filter tuned to detect circular symmetries, detection is done with a few ID convolutions. The detected eye center is used as input to our periocular algorithm based on retinotopic sampling grids and Gabor analysis of the local power spectrum. This setup is evaluated with two databases of iris data, one acquired with a close-up NIR camera, and another in visible light with a web-cam. The periocular system shows high resilience to inaccuracies in the position of the detected eye center. The density of the sampling grid can also be reduced without sacrificing too much accuracy, allowing additional computational savings. We also evaluate an iris texture matcher based on ID Log-Gabor wavelets. Despite the poorer performance of the iris matcher with the webcam database, its fusion with the periocular system results in improved performance.
Year
DOI
Venue
2014
10.1109/IWBF.2014.6914250
IWBF
Keywords
Field
DocType
Biometrics, periocular, eye detection, symmetry filters
Signal processing,Iris recognition,Computer vision,Computer science,Convolution,Filter (signal processing),Separable filter,Artificial intelligence,Iris flower data set,Grid,Wavelet
Conference
ISSN
Citations 
PageRank 
2381-6120
6
0.41
References 
Authors
20
2
Name
Order
Citations
PageRank
Fernando Alonso-Fernandez153137.65
Josef Bigün260.41