1. An electronic apparatus for detection of a face to recognize an iris of an eye, the apparatus comprising: receiving, by an image capturer of the electronic apparatus, a digital image of a user; and extracting, by a controller of the electronic apparatus, a characteristic vector from the image of the user, fitting, by the controller of the electronic apparatus, the extracted vector into a Pseudo 2D Hidden Markov Model (HMM) to train a face model having a plurality of states, and detect a face and facial features of the user; wherein the controller applies a directed acyclic graph (DAG) to the Psuedo 2D HMM on the electronic apparatus to localize the face of the user, and determines as localizing the face of the user when a transition path represented on the DAG comprises all of the plurality of states; wherein the controller calculates the transition path including states of the Psuedo 2D HMM, wherein the directed acyclic graph (DAG) includes super states of the face and sub states of each facial feature such that each node in the directed acyclic graph (DAG) is represented as states of the Psuedo 2D HMM, wherein the each node in the directed acyclic graph (DAG) is associated with a probability score that represents a score of a path passing through the node, wherein the node maximizing the probability score is an optimal node, given a HMM state sequence and a Pseudo 2D HMM trained face model, wherein the controller detects the face of the user, when an optimal path is found through the DAG, wherein a path traced out by the optimal node is the optimal path, wherein a node having the highest probability score is considered as the optimal node for an observation vector sequence.