Robust direction estimation of gradient vector field for iris recognition
As a reliable personal identification method, iris recognition has been receiving increasing attention. Based on the theory of robust statistics, a novel geometry-driven method for iris recognition is presented in this paper. An iris image is considered as a 3D surface of piecewise smooth patches. The direction of the 2D vector, which is the planar projection of the normal vector of image surface, is illumination insensitive and opposite to the direction of gradient vector. So the directional information of iris image's gradient vector field (GVF) is used to represent iris pattern. Robust direction estimation, direction diffusion followed by vector directional filtering, is performed on the GVF to extract stable iris feature. Extensive experimental results demonstrate that the recognition performance of the proposed algorithm is comparable with the best method in the open literature.