Scaling automation for bundled logs not only improves production efficiency, but also is a requirement for forest resource management. After image processing, diameter of each log and the number of logs is obtained, and this process is key point of scaling automation for bundled logs. Because the imaging environment of bundled logs is complex, much man-machine interaction is needed while using the existing methods for outline identification of bundled logs. In this paper, the color feature of logs in the image of cross section of bundled logs has been discussed, which is used to remove the irrelevant pixels in the image and obtain the pixels of logs. In the next step, Laplace filter is used to work out the edge in the image, implementing the separation of log outlines. Finally, we achieve outline identification of bundled logs.