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

Authors: Bineet Kaur; Sukhwinder Singh; Jagdish Kumar

Addresses: Department of Electronics and Communication Engineering, Punjab Engineering College (Deemed to be University), Chandigarh, 160012, India ' Department of Electronics and Communication Engineering, Punjab Engineering College (Deemed to be University), Chandigarh, 160012, India ' Department of Electrical Engineering, Punjab Engineering College (Deemed to be University), Chandigarh, 160012, India

Abstract: 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.

Keywords: biometrics; Dual-Hahn moments; iris recognition; Krawtchouk moments; orthogonal moments; periocular recognition; Tchebichef moments.

DOI: 10.1504/IJBM.2018.095293

International Journal of Biometrics, 2018 Vol.10 No.4, pp.352 - 367

Received: 03 Feb 2018
Accepted: 11 Jun 2018
Published online: 02 Oct 2018 *

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