Iris or Periocular? Exploring Sex Prediction from Near Infrared Ocular Images
Denton Bobeldyk, Arun A. Ross · 2016
Recent research has explored the possibility of automatically deducing the sex of an individual based on near infrared (NIR) images of the iris. Previous articles on this topic have extracted and used only the iris region, while most operational iris biometric systems typically acquire the extended ocular region for processing. Therefore, in this work, we investigate the sex-predictive accuracy associated with four different regions: (a) the extended ocular region; (b) the iris-excluded ocular region; (c) the iris-only region and (d) the normalized iris-only region. We employ the BSIF (Binarized Statistical Image Feature) texture operator to extract features from these regions, and train a Support Vector Machine (SVM) to classify the extracted feature set as Male or Female. Experiments on a dataset containing 3314 images suggest that the iris region only provides modest sex-specific cues compared to the surrounding periocular region. This research further underscores the importance of using the periocular region in iris recognition systems.