Multispectral palmprint recognition using steerable filter

This paper presents a multispectral palmprint recognition approach based on palm line orientation feature extracted with high order steerable filter. Gaussian function is used as isotropic window to design a high order steerable filter. The orientation features are selected as per dominant filter response for a particular orientation. Optimum values for parameters, i.e., standard deviation and number of orientations are found experimentally in order to obtain low equal error rate (EER) and high correct identification rate (CIR). Weighted score level fusion strategy is applied to combine the score of all spectral palmprints. A recognition rate of 99.97% is achieved with high decidability index (DI) and low EER. Further, the proposed approach is compared with traditional competitive code method for multispectral PolyU palmprint database.