Metal vapor plume and spatters are the important phenomena in the process of high power disk laser welding, and there exists a close relationship with the welding stability. The images of metal vapor plume and spatters which captured by a high speed camera during high power disk laser welding were analyzed in this experiment. Image processing techniques such as median filtering, Wiener filtering, gray level threshold and lightness transform were used to process the images so that the image characteristic parameters such as the area and number of spatters in an image, the average gray, mean value, variance and entropy of a spatter gray level image and the coordinate ratio of the centriod of plume and the welding point can be extracted. To reflect the actual welding results obviously by those characteristic parameters, K-L transform method was used to get a new set of characteristic parameters. Experimental results showed that this new set of characteristic parameters could reflect the actual welding effectively.
