一种基于误差扩散理论的直线检测算法

基于霍夫变换的基本原理,针对其在进行直线检测中存在的不足,利用误差扩散理论分析了在霍夫变换过程中的误差,研究了影响误差的因素.分析表明,直线的参数估计不仅和图像噪声有关,而且与直线的位置有关,直线到原点的距离越近,误差就越小,即对直线的检测精度就越高.提出了利用窗口移动的方法来寻求最优特征点和限制角度变换范围,结合最优特征点和误差扩散的理论,给出了一种改进的直线检测算法.在直线检测的精确性要求比较高的情况下,该算法能很好地满足要求.

A line detection algorithm based on error propagation

The principle of the traditional Hough transform was analyzed.Aiming at insufficiency of accuracy in line detection of the traditional Hough transform,using the principle of error propagation,analyses the error in the Hough transform in detail,obtains the factors influencing the error.The error not only depends on the noise of image,but also the distance of the line to origin,the closer to the origin,the smaller the error is.Presents the theory of using windows moving method to search the best-distinguished pixels and limit the scope transform.Combine the most best-distinguished pixels and error propagation,presents an improved line detection algorithm,this algorithm can improve the accuracy of the line detection by experiment.In the algorithm,the computational effective is not very good because of analyzing the error and finding the best-distinguished pixels,but for the application of high accuracy,the algorithm is good.