Comparative Analysis of Curve Reconstruction using Fuzzy C Means and Subtractive Clustering

被引:0
|
作者
Dureja, Ajay [1 ]
机构
[1] PDM Coll Engn, Dept Comp Sci & Engn, Bahadurgarh, India
来源
2018 INTERNATIONAL CONFERENCE ON RECENT INNOVATIONS IN ELECTRICAL, ELECTRONICS & COMMUNICATION ENGINEERING (ICRIEECE 2018) | 2018年
关键词
Interpolation; Curve Fitting; Clustering; Fuzzy C-mean; Subtractive;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Interpolation and curve fitting are the basic problems in the fields of computer graphics, image processing, and mathematical modeling of curves and surfaces. Another consideration problem in the field of reverse engineering is the reconstructing of a curve or a surface of geometric models from a point set. Curve fitting is helpful for surface reconstruction. Curve fitting can be described as computing the function g, given a set of input data sample points and to generate outputs corresponding to the inputs which is not specified earlier. There are various curve reconstruction techniques available and having their own advantages and disadvantages. In this paper, we try to find and simulate these techniques by making comparisons between some curve reconstruction techniques using clustering.
引用
收藏
页码:2249 / 2252
页数:4
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