A common procedure in digital postproduction is rotoscoping, the segmentation of independently moving foreground elements from background in a sequence of images. Still often carried out manually, rotoscoping is time-consuming and requires great skill in determining the boundary between foreground and background. Errors lead to a bubbling artifact in the final composited sequence. The industry is interested in automated rotoscoping. Any automatic segmentation method must correctly locate the boundary and be robust given rapid motion and non-static backgrounds. A cellular neural network for segmentation is presented that labels pixels by color, estimated motion and neighboring labels. The method is accurate, laborsaving and many times faster than manual rotoscoping.