Texture based palm Print recognition using 2-D Gabor filter and sub space approaches

Palm Print based biometric systems have attracted much attention in various security applications because palm prints are rich with unique line, point and texture patterns which even low resolution palm scanners can easily capture. This paper presents a texture based palm print recognition method which employ 2D Gabor filter to extract texture information from the central part of hand and use subspace methods for dimension reduction. The test and training images are compared in terms of calculating Euclidean distance between them. Algorithm is tested on standard benchmark databases (CASIA and IIT Delhi) and the results clarify the effectiveness of our method in terms of the Correct Recognition Rate and Computation Time.