Robust Log-Gabor Filter for Ear Biometrics
Robust Log-Gabor Filter for Ear Biometrics
Ears are a new biometric with major advantage in that they appear to maintain their structure with increasing age. Expanding on our previous parts-based model, we propose a new wavelet approach. In this, the log-Gabor filter exploits the frequency content of the ear boundary curves. Extending our model description, a specific aim of the new approach is to capture information in the ear’s outer structures. Ear biometrics is also concerned with the effects of partial occlusion, mostly by hair and earrings. By localization, intuitively a wavelet can offer performance advantage when handling occluded data. We also add a more robust matching strategy to restrict the influence of erroneous wavelet coefficients. Significant improvement is observed when we combine the model and the log- Gabor filter, and we will show that this improvement is maintained as the ears get occluded.
Arbab-Zavar, Banafshe
40e175ea-6557-47c6-b759-318d7e24984b
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
December 2008
Arbab-Zavar, Banafshe
40e175ea-6557-47c6-b759-318d7e24984b
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Arbab-Zavar, Banafshe and Nixon, Mark
(2008)
Robust Log-Gabor Filter for Ear Biometrics.
19th International Conference on Pattern Recognition (ICPR 2008), Tampa, United States.
08 - 11 Dec 2008.
Record type:
Conference or Workshop Item
(Poster)
Abstract
Ears are a new biometric with major advantage in that they appear to maintain their structure with increasing age. Expanding on our previous parts-based model, we propose a new wavelet approach. In this, the log-Gabor filter exploits the frequency content of the ear boundary curves. Extending our model description, a specific aim of the new approach is to capture information in the ear’s outer structures. Ear biometrics is also concerned with the effects of partial occlusion, mostly by hair and earrings. By localization, intuitively a wavelet can offer performance advantage when handling occluded data. We also add a more robust matching strategy to restrict the influence of erroneous wavelet coefficients. Significant improvement is observed when we combine the model and the log- Gabor filter, and we will show that this improvement is maintained as the ears get occluded.
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Robust_Log-Gabor_Filter_for_Ear_Biometrics.pdf
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Published date: December 2008
Venue - Dates:
19th International Conference on Pattern Recognition (ICPR 2008), Tampa, United States, 2008-12-08 - 2008-12-11
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 266781
URI: http://eprints.soton.ac.uk/id/eprint/266781
PURE UUID: cda17345-8f76-4cce-a0e9-0e80fd307de9
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Date deposited: 13 Oct 2008 09:54
Last modified: 15 Mar 2024 02:35
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Author:
Banafshe Arbab-Zavar
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