A novel 3D-2D computer vision algorithm for automatic inspection of filter components

This paper describes investigation results on the design of a real time, computer vision based system for automatic inspection of filter components in a manufacturing line. The problem involves reasoning about an object's 3D structure from 2D images. In computer vision, this is normally referred to as 3D-2D problem. In this paper, we first present a geometrical analysis of image correspondence vectors synthesized into a single coordinate frame. The analysis is based on geometrical considerations that are fundamentally different from analytical, perspective, or epipolar geometries. The camera setup stems from the geometrical implications of such analysis and from the given background knowledge of the task within the context of the production line. We then describe a novel geometrical algorithm to estimate parameters of interest that include depth estimation and the position and orientation of the camera in world coordinate frame. The algorithm provides the closed form solution to all estimated parameters making full use of distance between feature vectors and angle information. For a comparative study of algorithm performance, we also developed an algorithm based on epipolar geometry. Experimental results show that the geometrical algorithm performs significantly better than the algorithm based on epipolar geometry.