This paper presents methods for automated visual tracking of spatters in laser- and manual arc welding. Imaging of the welding process is challenging due to extreme conditions of high radiated light intensity variation. The formation and the number  of  spatters ejected in the welding process are dependent on the parameters of the welding process, and can potentially be used to tune the process towards better quality (either on-line of off-line). In our case, the spatter segmentation is based either on test on object elongatedness or Hough transform, which  are  applied  on pre-processed  image sequences captured by a high-speed smart camera. Part  of  the segmentation process (adaptive image capture and edge extraction) is performed on the camera, while the other parts of the algorithm are performed off-line in Matlab.  However, our intention is to move the computation towards the camera or an attached FPGA.