This paper proposes an innovative contactless palm print and knuckle print recognition system. We present a novel palm print and knuckle print tracking approach to automatically detect and capture these features from low resolution video stream. No constraint is imposed and the subject can place his/her hand naturally on top of the sensor without touching any device. Besides, we introduce a simple yet robust directional coding technique to encode the palm print feature in bit string representation. In addition, a new scheme is presented to extract knuckle print feature using ridgelet transform. Our method is different from the others in the sense that we do not resize the knuckle print images to standard size. The geometrical information of the knuckle print can thus be retained and utilized in our work. Support Vector Machine was used to fuse the scores output by the palm print and knuckle print experts. The fusion of these features yields promising result for real-time application.