| Abstract
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<p>We present a new system for biome … <p>We present a new system for biometric recognition using periocular images based on retinotopic sampling grids and Gabor analysis of the local power spectrum at different frequencies and orientations. A number of aspects are studied, including: 1) grid adaptation to dimensions of the target eye vs. grids of constant size, 2) comparison between circular- and rectangular-shaped grids, 3) use of Gabor magnitude vs. phase vectors for recognition, and 4) rotation compensation between query and test images. Results show that our system achieves competitive verification rates compared with other periocular recognition approaches. We also show that top verification rates can be obtained without rotation compensation, thus allowing to remove this step for computational efficiency. Also, the performance is not affected substantially if we use a grid of fixed dimensions, or it is even better in certain situations, avoiding the need of accurate detection of the iris region.</p>te detection of the iris region.</p>
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| Author
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Fernando Alonso-Fernandez +
, Josef Bigun +
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| Conference
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Swedish Symposium on Image Analysis 2013 (SSBA 2013), Gothenburg, 14-15 March
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| Diva
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http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:607423
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| PublicationType
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Conference Paper +
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| Title
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Biometric Recognition Using Periocular Images +
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| Year
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2013 +
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| Has queryThis property is a special property in this wiki.
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Publications:Biometric Recognition Using Periocular Images +
, Publications:Biometric Recognition Using Periocular Images +
, Publications:Biometric Recognition Using Periocular Images +
, Publications:Biometric Recognition Using Periocular Images +
, Publications:Biometric Recognition Using Periocular Images +
, Publications:Biometric Recognition Using Periocular Images +
, Publications:Biometric Recognition Using Periocular Images +
, Publications:Biometric Recognition Using Periocular Images +
, Publications:Biometric Recognition Using Periocular Images +
, Publications:Biometric Recognition Using Periocular Images +
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| Categories |
Publication +
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| Modification dateThis property is a special property in this wiki.
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30 September 2016 20:41:14 +
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