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Erschienen in:
2013 | OriginalPaper | Buchkapitel
A New Iris Recognition Approach Based on a Functional Representation
verfasst von : Dania Porro-Muñoz, Francisco José Silva-Mata, Victor Mendiola-Lau, Noslen Hernández, Isneri Talavera
Erschienen in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Verlag: Springer Berlin Heidelberg
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This paper proposes the introduction of annular Zernike polynomials for representing iris images data. This representation offers notables advantages like representing the images on a continuous domain that allows the application of Functional Data Analysis techniques, preserving their original nature. In addition, it provides a significant dimensionality reduction of the data, while it still has a high discriminative power. The proposed approach also deals with the occlusion problems that can be present in this type of images. In order to corroborate the effectiveness of the introduced approach, identification experiments were carried out. Iris international databases were used. Some of them are characterized by the presence of severe occlusion problems. Results have shown high recognition accuracy.