针对焊接过程中的图象处理问题，如检测焊缝边缘位置和确定焊接熔池的边缘大小和形状等问题，由于传统图象处理方法易受噪声和其他干扰信息的影响，因此很难准确及时地处理图象，为了克服此弱点，在比较了焊接过程中图象处理的微观算法和宏观算法的基础上，提出了运用分形理论的综合图象处理方法，该方法是根据焊接过程图象的特点，首先利用图象边缘的分形特征来进行区域分割，以便检测出图象边缘所在的模糊区域，然后用边缘检测方法的Laplace算子和最小二乘法拟合曲线来识别出图象的边缘，同时用该方法进行了实时焊接图象处理实验，实验结果证明，该方法不仅能准确识别出焊接焊缝或熔池图象的边缘，而且节省了图象处理的时间，为焊接过程的实时控制提供了可靠的信息。

In this paper the problems of image processing in welding process have been studied, for example, how to detect the edge position of welding seam and to ascertain the size and shape of welding pool and so on. The traditional method of image processing is sensitive to noise and other disturbances, so it is difficult to process images accurately and timely. In order to overcome this deficiency, microcosmic and macrocosmic algorithms of image processing in welding were compared in this paper, then a novel composite image processing method using fractal theory was put forward. Based on the characteristics of images of welding process, regions were divided up according to fractal characters of image edge, and fuzzy regions including image edges were detected, then image edges were recognized using Laplace operator and curved by LSM (least square method). Experiment results show that the image edge of welding seam or welding pool can be recognized correctly and quickly. The new developed image processing method could provide reliable information for the real time control of welding process.