Rigidity analysis from range image data for automatic inspection of filter components

Recent developments in computer vision and pattern recognition have enabled the development of sophisticated vision-based quality control systems for automatic inspection. We present a new geometrical analysis of rigid body transformation parameters from properties of reflected correspondence vectors. Based on this analysis, we propose a novel algorithm to calibrate transformation parameters of 3D objects in a fast production line of filter components. The algorithm performs a rigidity analysis from range images acquired from two cameras, making full use of distance and angle information providing a closed form solution to all parameters of interest. The method is used in conjunction with a decision support system where components falling outside specified thresholds are to be rejected. For a comparative study of algorithm performance, we also implemented a well known procedure for rigidity analysis based on quaternions. Experimental results demonstrate that our novel algorithm has a number of advantages over the quaternion method and that its performance is superior or similar to the quaternion method.