This paper presents a new approach for gesture classification using x- and y- projections of the image and optional depth features. The system uses a 3D Time-Of-Flight (TOF) sensor which has the big advantage of simplifying hand segmentation. For the presented system, a Photonic-Mixer-Device (PMD) camera with a resolution of 160 × 120 pixels and a frame rate of 15 frames per second is used. The goal of our system is to recognise 12 different static hand gestures. The x- and y- projections and the depth features of the captured image are good enough to use a simple nearest neighbour classifier, resulting in a fast classification. To evaluate the system, a set of 408 images is recorded, 12 gestures from 34 persons. With a 'Leave-One-Out' evaluation, the recognition rate of the system is 94.61% and the classification time is about 30 msec on a standard PC.