Object Segmentation Using Graph Cuts Based Edges Features

The paper presents a simple graph cuts algorithm based edges features to object segmentation problems. Graph cuts are used to find the global optimum of a cost function based on boundary and region of an image. The user gives some scribbles to background and foreground of an image. Gaussian mixture models(GMMs) are built based on the scribbles. The pixel without scribble belongs to the background or the foreground depending on the relative probability of each pixel. The contribution of our paper is to add edges features to GMMs. The approach is applied with images from the Grab cuts segmentation database. The approach is suitable for images with noise and in the foreground and background with similar colors.