A Colour Iris Recognition System Employing Multiple Classifier Techniques - radu, petru (ELCVIA Electronic Letters on Computer Vision and Image Analysis, 2013)
<span style="font-family: "Times","serif"; font-size: 11pt; mso-bidi-font-size: 10.0pt; mso-fareast-font-family: "Times New Roman"; mso-bidi-font-family: "Times New Roman"; mso-ansi-language: EN-GB; mso-fareast-language: ES; mso-bidi-language: AR-SA;">The randomness of iris texture has allowed researchers to develop biometric systems with almost flawless accuracies. However, a common drawback of the majority of existing iris recognition systems is the constrained environment in which the user is enroled and recognized. The iris recognition systems typically require a high quality iris image captured under near infrared illumination. A desirable property of an iris recognition system is to be able to operate on colour images, whilst maintaining a high accuracy. In the present work we propose an iris recognition methodology which is designed to cope with noisy colour iris images. There are two main contributions of this paper: first, we adapt standard iris features proposed in literature for near infrared images by applying a feature selection method on features extracted from various colour channels; second, we introduce a Multiple Classifier System architecture to enhance the recognition accuracy of the biometric system. With a feature size of only 360 real valued components, the proposed iris recognition system performs with a high accuracy on UBIRISv1 dataset, in both identification and verfication scenarios.