A weighting intersection point prediction iteration optimization algorithm used in photogrammetry for port hoisting machinery

Abstract

As a mature technology, photogrammetry is widely applied in today's engineering measurement field. However, because of the limitation of the port condition, it is impossible to obtain photos that are taken at ideal angles and distances when photogrammetry is used to measure port hoisting machinery, and this leads to invalid measurements with low accuracy data. To solve this problem, a new algorithm is proposed in this work. First, the proposed method introduces redundant measurements through an intersection point prediction algorithm to improve the measurement data’s accuracy. Second, a weighting algorithm based on the lens distortion model is then provided to further improve accuracy. Third, an iterative method is established from the threshold setting method based on the weighting algorithm. Thus, the quality of the final measurement could be controllable. Finally, an experiment is devised for the characteristics of the algorithm and the port condition. The results demonstrate that the method described in this paper significantly improves the accuracy of the measuring results of photogrammetry while photos used for the calculation were taken at unsatisfactory angles and distances caused by the limitation of the port condition.