This paper reports on a feasibility study of contactless hand biometrics using an RGB-Depth (RGB-D) camera such as the Kinect v2 prototype. The RGB, depth, and near-infrared (near-IR) spectra provide access to information such as palm print, hand shape, finger joint location, and vein patterns. Extraction of the hand is first done using depth data. The frames with the best palm position are selected, and then correlated into the synchronized RGB and near-IR frames for further processing of the related information in each spectra. Using the hand location information the palm can be extracted in the RGB data for use in palm recognition. Recognition of the palm is performed using Principle Component Analysis and K-Nearest-Neighbors for the classification. This multi-spectral analysis is a pre-requisite for hand shape, palm, and vein recognition to be integrated into a mass access control system or a personal computer secure access system.