Color Adjacency Modeling for Improved Image and Video Segmentation

Color models are often used for representing object appearance for foreground segmentation applications. The relationships between colors can be just as useful for object selection. In this paper, we present a method of modeling color adjacency relationships. By using color adjacency models, the importance of an edge in a given application can be determined and scaled accordingly. We apply our model to foreground segmentation of similar images and video. We show that given one previously-segmented image, we can greatly reduce the error when automatically segmenting other images by using our color adjacency model to weight the likelihood that an edge is part of the desired object boundary.