基于遗传算法的B样条曲线拟合改进算法

B-spline curve fitting is applied to draw the changing trend of discrete data points, which usually obtains by data approximation or iterative method. It plays an important part in image processing and reverse engineering. Aiming at the situations where multi peak, cuspidal point or discontinuity exists in the curve to fit, this paper proposed a B-spline curve fitting algorithm based on genetic algorithm. Firstly it used the penalty function to transform the constrained optimization problem into an unconstrained problem. Then it used an improved genetic algorithm to select an adaptive fitness function, and adjusted the number and positions of nodes adaptively by combining the simulated annealing algorithm to find the optimal node vector. The iterations continued until generating the final good reconstruction curve. Experimental results show that the algorithm improves accuracy and speeds up convergence effectively.