Analyzing Covariate Influence on Gender and Race Prediction from Near-Infrared Ocular Images

Understand

Recent research has explored the possibility of automatically deducing information such as gender, age and race of an individual from their biometric data.

• While the face modality has been extensively studied in this regard, the iris modality less so.
• In this paper, we first review the medical literature to establish a biological basis for extracting gender and race cues from the iris.
• Then, we demonstrate that it is possible to use simple texture descriptors, like BSIF (Binarized Statistical Image Feature) and LBP (Local Binary Patterns), to extract gender and race attributes from an NIR ocular image used in a typical iris recognition system.