The main objective of this thesis is the development and feasibility testing of a proposed multispectral contactless hand biometric authentication system based on the Kinect v2 sensor. To achieve the goal of contactless authentication the hand images of the user are extracted in the red-green-blue, near-infrared, and depth spectra in real time. These extracted frames are then passed through an eigenhands based recognition system. To ensure the results carry across different classification methods both K-Nearest-Neighbours and Support Vector Machines are tested. The proposed hand recognition system is tested using a locally collected database of many different users recorded in the three spectra available using the Kinect v2 sensor. Through experimentation with the collected database and validation of the parameters used in the classification methods the feasibility of the proposed hand recognition system is proven.