Iris Recognition Using Level Set and Local Binary Pattern
B. Connor, Kaushik Roy · International Journal of Computer Theory and Engineering · 2014
This paper presents an efficient algorithm for iris recognition using the Level Set (LS) method and Local Binary Pattern (LBP).We deploy a Distance Regularized Level Set (DRLS)-based iris segmentation procedure in which the regularity of the Level Set (LS) function is intrinsically maintained during the curve propagation process.The LS evolution is derived as the gradient flow that minimizes energy functional with a distance regularization term and an external energy that drives the motion of the zero LS toward iris boundary accurately.DRLS also uses relatively large time steps in the finite difference scheme to reduce the curve propagation time.The deployed variational model is robust against poor localization and weak iris/sclera boundaries.Furthermore, we apply a Modified LBP (MLBP) in an effort to elicit the iris feature elements.The MLBP combines both the sign and magnitude features for the improvement of iris texture classification performance.The identification and verification performance of the proposed scheme is validated using the CASIA version 3 interval dataset.