Efficient image segmentation incorporating photometric and geometric information

This paper proposes a new segmentation approach based on graph cuts. However, we take advantage of it in a different way using photometric (color and texton) and geometric information to analyze and segment images. These additional information provide better knowledge of the image's internal structure. Hence, they lead to a significant improvement in segmentation quality, while require fewer instruction from user interactions. Some experimental results are presented in the variety contexts of image segmentation giving high accurate segmentation comparing with other methods.