Fusing 3D Gabor and Block-Wise Spatial Features for Hyperspectral Palmprint Recognition

Hyperspectral palmprint contains various information in the joint spatial-spectral domain. One crucial task in hyperspectral palmprint recognition is how to extract spatial-spectral features. Since hyperspectral palmprint is three dimensional, most of the existing 2D based algorithms, such as collaborative representation (CR) based framework [15], may not fully explore the information on the spectral domain. Although 3D Gabor filter [18] can be utilized to encode the information on the joint spatial-spectral domain, the texture direction information such as the surface map may not be explored sufficiently. In this work, a novel response-competition (ResCom) feature is proposed to present the spectral information of hyperspectral palmprint based on 3D Gabor filters. Incorporated with the 2D surface map, the ResCom feature can encode not only the 2D texture but also the 3D response variation. Therefore, features of hyperspectral palmprint will be extracted efficiently on the joint spatial-spectral domain. By fusing Block-wise and ResCom features, the proposed approach achieves so far the highest recognition rate of 99.43% on the public hyperspectral palmprint database.