Automatic trimap generation for digital image matting

Digital image matting is one of the most popular topics in image processing in recent years. For most matting methods, trimap serves as one of the key inputs, and the accuracy of the trimap affects image matting result a lot. Most existing works did not pay much attention to acquiring a trimap; instead, they assumed that the trimap was given, meaning the matting process usually involved users' inputs. In this paper, an automatic trimap generation technique is proposed. First, the contour of the segmentation result is dilated to get an initial guess of the trimap followed by alpha estimation. Then, a smart brush with dynamic width is performed by analyzing the structure of the foreground object to generate another trimap. In other words, the brush size is enlarged if the object boundary contains fine details like hair, fur, etc. On the contrary, the brush size gets smaller if the contour of the object is just a simple curve or straight line. Moreover, by combining the trimap obtained in step one and downsampling the image, the uncertainty is defined as the blurred region, and the third trimap is formed. The final step is to combine these three trimaps together by voting. The experimental results show that the trimap generated by the proposed method effectively improves the matting result. Moreover, the enhancement of the accuracy of the trimap results in a reduction of regions to be processed, so that the matting procedure is accelerated.