计算机科学 ›› 2012, Vol. 39 ›› Issue (Z6): 482-484.

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最小二乘法分段直线拟合

田 垅,刘宗田   

  1. (上海大学计算机工程与科学学院 上海200072)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Least-squares Method Piecewise Linear Fitting

  • Online:2018-11-16 Published:2018-11-16

摘要: 曲线拟合是图像分析中非常重要的描述符号。最常用的曲线拟合方法是最小二乘法,然而一般的最小二乘法有一定的局限性,已经有不少学者对其进行了一些改进。进一步对最小二乘法进行改进,提出一种新的分段直线拟合算法来代替多项式曲线拟合,以达到简化数学模型的建立和减少计算的目的,使其能够更好地对点序列进行拟合。

关键词: 直线拟合,最小二乘法,分段

Abstract: Curve fitting is a very important descriptor in image analysis, the most commonly used curve fitting method is least squares method. But ordinary least squares method has some limitations, and there are many scholars have made study of improving it. The authors made further improvement on least-squares method and proposed a new piecewise linear fitting algorithm instead of polynomial curve fitting. The new algorithm achieves the goal of simplifying the mathematical model, reducing the calculation, and makes it better to fit point sequence.

Key words: Linear fitting,Lcast-squares method,Piccewisc

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