Iris Identification Based on a Local Analysis of the Iris Texture
| Autor: | Florence Rossant, Beata Mikovicova, Mathieu Adam, Frederic Amiel |
|---|---|
| Přispěvatelé: | Centre d'études techniques de l'équipement Ouest (CETE Ouest), Avant création Cerema, ISEP, Institut Supérieur d'Electronique de Paris (ISEP), Département d'électonique, Institut Supérieur d'Electronique de Paris-ISEP |
| Jazyk: | angličtina |
| Rok vydání: | 2009 |
| Předmět: |
business.industry
Feature extraction Iris recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Image segmentation A-weighting Geography medicine.anatomical_structure Image texture Local analysis [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing medicine Segmentation Computer vision Artificial intelligence Iris (anatomy) business |
| Zdroj: | 2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis ISPA ISPA, Sep 2009, Salzburg, Austria. ⟨10.1109/ISPA.2009.5297683⟩ |
| DOI: | 10.1109/ISPA.2009.5297683⟩ |
| Popis: | International audience; This paper focuses on a new iris identification method based on a local analysis of the iris texture. In the method, the iris is divided in sub-regions, using locally sliding windows, to extract local signatures. Local distances are then calculated and fused, based on a weighting average. The sliding allows to compensate for local distortions due to segmentation imprecision. The applied weights take into account additional knowledge about the information quantity carried by the different sub-regions and its reliability. Tests have been conducted on the CASIA-IrisV3-Interval database. They show good performances of the new method. Similar or even better results are obtained, compared to published ones, with a set of iris containing twice more subjects. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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