Phase Intensive Global Pattern for periocular recognition

Partially constrained human recognition through periocular region has emerged as a new paradigm in biometric security. This article proposes Phase Intensive Global Pattern (PIGP): a novel global feature based on variation of intensity of a pixel-neighbours with respect to different phases. The feature thus extracted is claimed to be rotation invariant and hence useful to identify human from images with face-tilt. The performance of proposed feature is experimented on UBIRISv2 database, which is a very large standard dataset with unconstrained periocular images captured under visible spectrum. The proposed work has been compared with Circular Local Binary Pattern (CLBP), and Walsh Transform, and experimentally found to yield higher accuracy, though with increased computation complexity and increased size of the feature vector.