Spectral matting based on color information of matting components

Abstract

Color information carried by the matting components in spectral matting is used in our method to solve the matting problem. By comparing the color similarity of each matting component, the matting components were separated into two groups: the foreground and the background. There are two advantages of doing so. Firstly, there is no need to use the trimap which is a necessary tool in traditional matting solving methods to accomplish the process of semi-supervised learning. Instead, the color similarity information could be used as constrain or heuristic cue in finishing the process of unsupervised learning to lower the blindness of automatically extracting the foreground object. Secondly, combining the color similarity information with a little user provided foreground and background cue could further reduce the number of matting components whose group have not been known yet, and thus a semi-supervised learning process which could only be done by using a lot user provided cue in traditional matting solving methods could be accomplished. © 2010 Springer-Verlag Berlin Heidelberg.