Smoothing of SFS Reconstructed Surface Based on Genetic Algorithm

Abstract

To improve the smoothness of SFS reconstructed surface, a new approach based on genetic algorithm is proposed. First, by analyzing the principle of SFS, the reason for surface error and distortion zone are found. By adding data according to the symmetric and asymmetric principle and B spline, data in the distortion zone are added and the reconstruction of SFS is realized. The evaluation criteria for smoothness of curves and surfaces are given according to the mathematical sense and concurrent level of CAGD/CAD/CAM. The surface smoothing process is turn into two curve smoothing process in two directions. The evaluation criteria is taken as the constraint condition and then the smoothing of SFS reconstructed surface based on the genetic algorithm is realized. The experimental results show that this new approach is an effective way to eliminate the bad points of SFS surface, improve the surface quality so it is a practical method for surface smoothing.