计算机工程与应用 ›› 2012, Vol. 48 ›› Issue (15): 192-194.

• 图形、图像、模式识别 • 上一篇    下一篇

基于SOM网络的三次B样条曲线重建

王世东1，2，王焕宝3   

  1. 1.安徽建筑工业学院 信息网络中心，合肥 230022
    2.中国科学技术大学 火灾科学国家重点实验室，合肥 230026
    3.安徽建筑工业学院 数理系，合肥 230022
  • 出版日期:2012-05-21 发布日期:2012-05-30

Cubic B-spline curve reconstruction based on SOM

WANG Shidong1，2, WANG Huanbao3   

  1. 1.Information Network Center, Anhui University of Architecture, Hefei 230022, China
    2.State Key Lab of Fire Science, University of Science and Technology of China, Hefei 230026, China
    3.Department of  Mathematics, Anhui University of Architecture, Hefei 230022, China
  • Online:2012-05-21 Published:2012-05-30

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摘要： 使用散乱点集重建曲线曲面，在逆向工程和计算机视觉中有着广泛的应用。提出基于SOM网络的三次B样条曲线重建算法。给定某一曲线散乱点集和一初始神经网络，优化SOM网络中神经元位置，使网络逼近散乱点和映射散乱点空间特征。用特征点反求三次B样条曲线控制点，利用控制点重建三次B样条曲线。试验结果表明，算法取得的曲线重建效果良好。

关键词: 自组织映射网络, 散乱点, 特征点, B样条

Abstract: Curve and surface reconstruction based on unorganized data points plays an important role in the fields of reverse engineering and computer vision. This paper presents a new algorithm based on SOM to realize Cubic B-spline reconstruction. A set of unorganized data points and an initial neural network are given. The network can be optimized using the algorithm to make the neurons gradually approach the given unorganized data points and reflects spatial characteristics of unorganized data points. Control points of cubic B-spline curve are reversely calculated using the dominant points. Some experiment results show that the new algorithm is quite effective.

Key words: Self-Organizing Map（SOM）, unorganized data points, dominant points, B-spline

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