Automatic camera placement in vision metrology based on a fuzzy inference system

Automatic determination of the Camera placement for measuring complex industrial objects by vision metrology systems is a real challenge if the 3D simulated CAD models of the object along with the workspace information are not available. In such a case, several uncertain parameters such as visibility, accessibility, and camera-object distance are introduced into the camera placement decision-making that make it a non-deterministic complicated process. Hence, the uncertain behavior of the vision constraints demands the use of the fuzzy logic inference approach for the camera placement network design. In this paper, a novel method based on fuzzy logic reasoning strategy is proposed for the accuracy enhancement of an existing photogrammetric network by automatically adding new exposures. The fuzzy system is designed to make use of human type reasoning strategy by incorporating appropriate rules. The results indicate the high potential of the proposed method for automatic sensor placement in vision metrology.