Best Regions for Periocular Recognition with NIR and Visible Images
2014 (English)In: 2014 IEEE International Conference on Image Processing (ICIP), Piscataway, NJ: IEEE Press, 2014, 4987-4991 p.Conference paper (Refereed)
We evaluate the most useful regions for periocular recognition. For this purpose, we employ our periocular algorithm based on retinotopic sampling grids and Gabor analysis of the spectrum. We use both NIR and visible iris images. The best regions are selected via Sequential Forward Floating Selection (SFFS). The iris neighborhood (including sclera and eyelashes) is found as the best region with NIR data, while the surrounding skin texture (which is over-illuminated in NIR images) is the most discriminative region in visible range. To the best of our knowledge, only one work in the literature has evaluated the influence of different regions in the performance of periocular recognition algorithms. Our results are in the same line, despite the use of completely different matchers. We also evaluate an iris texture matcher, providing fusion results with our periocular system as well.
Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Press, 2014. 4987-4991 p.
Biometrics, periocular, eye, Gabor filters
IdentifiersURN: urn:nbn:se:hh:diva-25468DOI: 10.1109/ICIP.2014.7026010ISBN: 978-1-4799-5751-4ISBN: 978-1-4799-5751-14OAI: oai:DiVA.org:hh-25468DiVA: diva2:720821
IEEE International Conference on Image Processing, ICIP, Paris, France, 27-30 October, 2014
FunderSwedish Research Council, 2012-4313