Measurement Error Control Of Feature Points Photographing

Based on the demand and application of 3D critical points measurement, this paper analyzes the principle and features of the system of typical 3D measurement at home and abroad. Directed towards TNFP, the feature point optical measurement system, this paper focuses on the error source and control method in the process of camera calibration and 3D reconstruction.On the basis of existing camera calibration algorithm of TNFP, a new camera calibration algorithm grounding on factorization is proposed, further more, a reverse distortion correction based on existing optical distortion model is proposed, this correction achieves direct linear transformation from image detected coordinates to ideal detected image coordinates. Experiments show that the measurement accuracy can be obviously improved by optimizing the camera calibration algorithm.In the process of 3D reconstruction, a reconstructed strategy based on standard view is proposed to eliminate the impact of accumulated error. This kind of reconstructed strategy can effectively decrease the accumulated error caused from coordinate transformation. In the 3D measurement to large objects, topological constraint and the strategy of orientating first then reconstructing are proposed to further control the accumulated error. By adopting the combined adjustment technology, the measurement range of TNFP system is within 4m×3m×2m, while the overall measurement error is less than 0.2mm/m.