Networked data fusion based on visual measure system with single camera

In view of the fact that the visual measure system with single camera can not measure the shield between the measured objects each other, a networked technique was proposed for this kind of measure system. The optical characteristic spots on every network control point were measured by the single camera measure system, and the measured coordinates were normalized into the same world coordinate system to get the global data, and the overall measurement was achieved. Applying the weighted data fusion algorithm, distributing the weight factors according to the stability theory of eigenvector, fusing the global normalized space coordinates, and the ultimate expression of fusion estimate was derived. The experiment in comparison to the simulation was performed in a CMM and the results showed that the maximal absolute error of the space coordinates is 0.035 mm after normalization by quaternion and Euler angles algorithms. The proposed algorithm appears more accurate and more stable than the point set center fusion algorithm, and in the application of networked normalization of measure system, the quaternion algorithm is better than the Euler angles algorithm.