Fusing iris and periocular recognition using discrete orthogonal moment-based invariant feature-set

Iris recognition in uncontrolled environment poses a challenge due to occlusion noise, specular reflections and poor resolution. Therefore, periocular recognition has become a popular biometric modality which when used with iris recognition makes the system suitable for high security applications. The paper introduces discrete orthogonal moment-based invariant features: Tchebichef, Krawtchouk and Dual-Hahn moments which provide discriminative features with compact information and minimum redundancy for non-ideal conditions. The proposed techniques are applied on two publicly available iris databases: IITD v1 and UBIRIS v2 and our own PEC, Chandigarh periocular database. Results demonstrate that the moment-based feature-set outperforms existing approaches available in the literature.