In this paper, we propose to investigate the role of a new descriptor named Kernel Descriptor (KDES), recently introduced in [1] for hand posture recognition. As the hand posture has it own the color characteristic, we will examine kernel descriptor in diffident color channels such as HSV, RGB, Lab to find out the most suitable color space for kernel representation of hand posture. We perform extensive experiments on two datasets. The obtained results are promising (97.3% on NUS-2 dataset and 85.0% on our dataset). Thank to the analysis, kernel descriptor is highly recommended for hand posture recognition.