A simple stroke-based iterative image matting approach
一种基于简单笔画交互的迭代图像抠图方法

To reduce labors such as user input, this paper proposes a simple stroke-based iterative image matting approach, which only needs a few user scribbles to mark foreground and background pixels. It builds robust color models from multiple feature spaces of pixels, and further introduces sampling constraint functions to collect valid foreground and background samples. By combing samples information and local smoothness constraint, the method defines a global energy function on all unknown pixels. The optimal matte is accomplished with iterative energy minimization. The experimental results demonstrated that the method can produce accurate and visually smooth results and is efficient to handle texture-rich images or images with ambiguous foreground and background colors.