A Fast Object Extraction Method Based on Color and Texture Information
MU Ya · Chinese Journal of Computers · 2009
In recent years researchers have developed many algorithms for object extraction and image matting. However,previous approaches usually require trimaps as input,or consume intolerably long time to get the final results,and most of them just consider the color information. This paper proposes a novel fast hierarchical object extraction method. First the input image is segmented roughly into two regions: foreground and background,using a modified hierarchical Graph Cuts algorithm. After that,the opacity values for the pixels nearby the foreground/background border are estimated using belief propagation (BP). Unlike traditional BP-based approaches,besides the smoothness and color constraints,the texture information is introduced by building grayscale co-occurrence matrices. Moreover,considering the fact that the resolution of photographs taken by digital cameras continues to increase at a rapid and steady pace,the modified version of hierarchical Graph Cuts proposed in this paper could accelerate the above-mentioned computation process,getting a comparably satisfactory local optimal solution as previous approaches. Experiments show that the method is effective and efficient especially for large images.