One of the most challenging issues in iris recognition is the design of techniques able to ensure high accuracy even in adverse conditions. This paper deals with an approach to iris matching based on the combination of local features: Linear Binary Patterns (LBP) and discriminable textons (BLOBs) are presently exploited. The techniques have been refined ad hoc, to allow the extraction of significant discriminative features, even with images captured in variable visible light conditions, and affected by noise due to distance/resolution or to scarce user collaboration (blurring, off-axis iris, occlusion by eyelashes and eyelids). The obtained results strongly motivate further investigations along this line, most of all the addition of more local features.
Noisy Iris Recognition Integrated Scheme / Maria De, Marsico; Michele, Nappi; Riccio, Daniel. - In: PATTERN RECOGNITION LETTERS. - ISSN 0167-8655. - 33:8(2012), pp. 1006-1011. [10.1016/j.patrec.2011.09.010]
Noisy Iris Recognition Integrated Scheme
RICCIO, Daniel
2012
Abstract
One of the most challenging issues in iris recognition is the design of techniques able to ensure high accuracy even in adverse conditions. This paper deals with an approach to iris matching based on the combination of local features: Linear Binary Patterns (LBP) and discriminable textons (BLOBs) are presently exploited. The techniques have been refined ad hoc, to allow the extraction of significant discriminative features, even with images captured in variable visible light conditions, and affected by noise due to distance/resolution or to scarce user collaboration (blurring, off-axis iris, occlusion by eyelashes and eyelids). The obtained results strongly motivate further investigations along this line, most of all the addition of more local features.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.