Foreground-background segmentation by cellular neural networks
P.R. Giaccone, Dimitris Tsaptsinos, G.A. Jones · 2002
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 our manually, rotoscoping is time-consuming and requires great skill in determining the boundary between foreground and background. Errors lead to a bubbling artefact 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 colour, estimated motion and neighbouring labels. The method is accurate, labour saving and many times faster than manual rotoscoping.