Recognition of Sclera through probabilistic model

Abstract

To propose a new approach for human ID: sclera recognition. Second, we developed a new method for
sclera segmentation which works for color images. Third, we designed a Gabor wavelet-based sclera pattern
enhancement method to emphasize and binarize the sclera vessel patterns. Finally, we proposed a line-descriptor
based feature extraction, registration, and template matching method that is illumination, scale, orientation, and
deformation invariant and can mitigate the multilayered deformation effects and tolerate segmentation error.