The popular eigenfaces-based face recognition among proposed face recognition methods utilizes the eigenfaces obtained from applying PCA to a training face image set. Thus, it may not achieve a reliable performance under illumination environments different from that of training face images. In this paper, we propose an illumination-separate eigenfaces-based face recognition method, which excludes the effects of illumination as much as possible. The proposed method utilizes the illumination-separate eigenfaces which is obtained by orthogonal decomposition of the eigenface space of face model image set with respect to the constructed face illumination subspace. Through experiments, it is shown that the proposed face recognition method based on the illumination-separate eigenfaces performs more robustly under various illumination environments than the conventional eigenfaces-based face recognition method.