In this paper an iris detection scheme for noisy images acquired by means of mobile devices is presented. Iris segmentation is accomplished by exploiting the use of the watershed transform with the purpose of identifying the iris boundary as much precisely as possible. After a pre-processing step aimed at color/illumination correction, the watershed transform is computed and suitably binarized. Circle fitting is then accomplished to identify the limbus boundary by using curvature approximation and a cost function for circle scoring. The watershed transform is furthermore employed to distinguish, in the zone delimited by the best fitting circle, the regions actually belonging to the iris from those belonging to eyelids and sclera. Finally, pupil detection is accomplished by means of circle fitting and by using a voting function based on homogeneity and separability criteria. The suggested iris detection scheme has a positive impact on an the accuracy in computing the iris code, which has in turn a positive impact on the performance of iris recognition.

IDEM: Iris DEtection on Mobile devices / Maria, Frucci; Chiara, Galdi; Michele, Nappi; Riccio, Daniel. - (2014), pp. 1752-1757. (Intervento presentato al convegno International Conference on Pattern Recognition tenutosi a Stoccolma, Svezia nel 24-28/08/2014) [10.1109/ICPR.2014.308].

IDEM: Iris DEtection on Mobile devices

RICCIO, Daniel
2014

Abstract

In this paper an iris detection scheme for noisy images acquired by means of mobile devices is presented. Iris segmentation is accomplished by exploiting the use of the watershed transform with the purpose of identifying the iris boundary as much precisely as possible. After a pre-processing step aimed at color/illumination correction, the watershed transform is computed and suitably binarized. Circle fitting is then accomplished to identify the limbus boundary by using curvature approximation and a cost function for circle scoring. The watershed transform is furthermore employed to distinguish, in the zone delimited by the best fitting circle, the regions actually belonging to the iris from those belonging to eyelids and sclera. Finally, pupil detection is accomplished by means of circle fitting and by using a voting function based on homogeneity and separability criteria. The suggested iris detection scheme has a positive impact on an the accuracy in computing the iris code, which has in turn a positive impact on the performance of iris recognition.
2014
978-147995208-3
IDEM: Iris DEtection on Mobile devices / Maria, Frucci; Chiara, Galdi; Michele, Nappi; Riccio, Daniel. - (2014), pp. 1752-1757. (Intervento presentato al convegno International Conference on Pattern Recognition tenutosi a Stoccolma, Svezia nel 24-28/08/2014) [10.1109/ICPR.2014.308].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/588218
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