霍夫变换与最小二乘法相结合的直线拟合

Fit Line Using A Method Combined Hough Transform With Least Square

将霍夫变换与最小二乘法相结合 ,研究对实验数据和图像处理中的二值边缘图进行直线拟合的方法。首先 ,用霍夫变换剔除数据点集中的干扰点或噪声 ,并将分布在不同直线附近的点分离出来 ;然后 ,用最小二乘法拟合各直线。该方法既解决了直接使用最小二乘法拟合时 ,拟合直线易受干扰点或噪声的影响和数据点分布在多条直线附近而无法拟合的两个问题 ;同时也解决了直接使用霍夫变换时 ,拟合直线精度不高和直线段有效区间不容易控制的问题。

A new approach to fit line is proposed. In this method, Hough transform and least square have been combined to process experiment data and the contour of binary images. Firstly, interferential points and noise in the set of data points have been deleted by using Hough transform, meanwhile the points in the vicinity of different lines are separated; Secondly, lines have been fit by using least square. When fitting line using least square, it always encounters some problems. On the one hand, it can't overcome the interference of interferential points and noise, on the other hand, when data points distributed in the vicinity of a few lines, it is difficult to fit line based on these points. When fitting lines using Hough transform, it tends to have low precision and difficult to control line in the valid trivial. The presented method can overcome these problems. The effectiveness of the algorithm is demonstrated by the experiment.