为了获得精确的和视觉上连续的抠图结果，提出了一种基于简单笔画的图像抠图方法，该方法仅需要用户以少量笔画和拖拽矩形框的方式指定前景和背景像素即可实现。该方法从亮度，纹理和空间位置多特征空间考虑像素的分布，首先建立了鲁棒的颜色分布模型；然后在此基础上，定义采样约束函数，再来获取精确的前景和背景样本；最后基于样本信息和平滑性约束，为所有未知像素构造了一个全局的能量函数，再通过迭代的优化将用户约束传播到整个未知区域。实验结果表明，该方法不仅保持了抠图结果的精确性和视觉上的连续性，并能够有效地处理纹理丰富和具有相似的前景与背景颜色的输入图像。

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.