This paper proposes a 2D face recognition algorithm using phase-based correspondence matching. The phase information obtained from 2D DFT (Discrete Fourier Transform) of images contains important information of image representation. The phase-based image matching is successfully applied to sub-pixel image registration tasks for computer vision applications and image recognition tasks for biometric authentication applications. Hierarchical block matching using phase information, i.e, phase-based correspondence matching, can find the corresponding points on the input image from the reference points on the registered image with sub-pixel accuracy. For face recognition, the phase-based correspondence matching is useful for minute change of texture, such as facial expression change, illumination change, etc. Experimental evaluation using the CSU Face Identification Evaluation System with the FERET database demonstrates efficient recognition performance of the proposed algorithm compared with the conventional face recognition algorithms.