Efficient palmprint identification using novel symmetry filter and alignment refinement

This paper presents a robust algorithm for line orientation code-based palmprint identification in which we propose a novel symmetry filter and an efficient alignment refinement technique. The main idea of the symmetry filter is to compute the approximate magnitude of the Gabor filter based on the modified finite Radon transform MFRAT, the so-called GMFRAT filter. The advantages of GMFRAT filters are that: 1 they are capable of quickly computing orientation codes; 2 they remarkably reduce remarkably the sizes of these features. The alignment refinement technique, which uses local orientation patterns, is also proposed to solve the problem of rotations and translations caused by an imperfect preprocessing phase. Based on our alignment refinement, the matching algorithm is designed. The experimental results obtained using the public databases of the Hong Kong Polytechnic University and the Indian Institute of Technology Delhi demonstrate the effectiveness of the proposed method.