Interactive Segmentation of Color Images Based on Color Saliency

SUMMARY Efficient interactive foreground extraction from color images is of great practical importance in computer vision. In recent years, an approach based on optimization using graph-cuts has been widely used. However, an interactive foreground extraction approach, which is intuitive and efficient for users, is required for practical applications. In this paper, we propose a novel interactive foreground extraction method based on color saliency. In our method, the user provides only some foreground pixels as the initial reference. To achieve extraction of multiple target objects, the likelihoods of the foreground and background are defined by a Gaussian mixture model and a color saliency map based on the provided reference pixels. These likelihoods are added to the cost of the proposed graph. Finally, image segmentation is performed by optimizing the proposed graph using the graph-cut algorithm.