李道伦, 卢德唐, 孔祥言. 基于径向基函数网络的隐式曲线[J]. 计算机研究与发展, 2005, 42(4): 599-603.
 引用本文: 李道伦, 卢德唐, 孔祥言. 基于径向基函数网络的隐式曲线[J]. 计算机研究与发展, 2005, 42(4): 599-603.
Li Daolun, Lu Detang, Kong Xiangyan. Implicit Curve Based on Radial Basis Function Network[J]. Journal of Computer Research and Development, 2005, 42(4): 599-603.
 Citation: Li Daolun, Lu Detang, Kong Xiangyan. Implicit Curve Based on Radial Basis Function Network[J]. Journal of Computer Research and Development, 2005, 42(4): 599-603.

Implicit Curve Based on Radial Basis Function Network

• 摘要: 将径向基函数网络与隐式曲线构造原理相结合，提出了构造隐式曲线的新方法，即首先由约束点构造神经网络的输入与输出，把描述物体边界曲线的隐式函数转化为显式函数，然后用径向基函数网络对此显式函数进行逼近，最后由神经网络的仿真曲面得到物体边界的拟合曲线.实验表明，基于径向基函数网络的隐式曲线具有很强的物体边界描述能力和缺损修复能 力.

Abstract: A new method for closed curve construction is introduced, which is based on the combination of RBF (radial basis function) neural network and the principle of i mplicit curve construction. The algorithm, firstly, constructs the input and output of the RBF neural network from the constraint points, secondly changes the implicit function that represents object boundary into explicit function, thirdly uses RBF neural network to fit the curve of the explicit function, and finally obtains the fitting curves that represent the object boundary from the simulation surface. The main difference between the new method and other methods is that it is unnecessary for the new method to minimize the sum of the squares of the E uclidean distance or to solve linear system. The method not only has better resu lts than the method based on BP neural network, and also has some merit of local ity that other methods do not have. It has good numerical stability and robustne ss in dealing with noisy or missing data. Experimental results are given to veri fy the effectiveness of recovering incomplete images and object boundary reconst ruction.

/

• 分享
• 用微信扫码二维码

分享至好友和朋友圈