Today's industrial automation of spray painting is limited to high part volumes and robot trajectories that are programmed by off-line programming and manual teach-in. This paper presents an approach that uses range image data to obtain the geometry of an unknown part and to automatically generate the robot spray painting trajectories. Laser strip range sensors are installed in front of the paint booth to acquire a range image of the part. Utilizing process knowledge (a geometric library containing constraints specific for the painting application) geometric primitives are detected in the range data. From the geometric primitives a normal vector field is generated that enables to extract main faces. The main faces are located in a 3D space and the process knowledge related to each geometric primitive is utilized to obtain the trajectory for the paint gun. Results of painting a car mirror and steering column are given.