An improved line-based face recognition and indexing algorithm

Much research in human face recognition involves fronto-parallel face images, constrained rotations in and out of the plane, and under strict imaging conditions such as controlled illumination. In this paper, we propose an improved line-based face recognition and indexing algorithm that uses a set of selected rectilinear line segments of 2D face image views as the underlying image representation, together with a nearest-neighbor classifier as the line matching scheme. The algorithm achieves high generalization recognition rates for rotations both in and out of the plane and is robust to scaling and variant illumination.