关键词: 曲面匹配, 误差评估, 遗传算法, 最小二乘法

Abstract:

The iterative closest point (ICP) surfaces matching algorithm based on the least square criterion leads to biggish errors when there are local high distortions in the surface to be valued. A new algorithm based on Genetic Algorithm and least square criterion were proposed in this paper. To insure the result be a global optimization, a Genetic Algorithm was used to get an appropriate initial position. With the result of ICP algorithm, an error threshold was constructed to filtrate the points set, in this way, the local high distortions points were eliminated, and then the transform matrix was gotten. Transforming the initial points set with the matrix, a perfect matching result could be achievied. The following examples showed that the matching results were better than those of the routine ICP method.

Key words: surfaces matching, error evaluation, genetic algorithm, least square