Fast Image Segmentation Algorithm Combining CS-LBP Texture Features
Yi Liu, Huang Bing, Huaijiang Sun, Xia De-shen · 2013
Graph cuts algorithm is one of the most effective interactive image segmentation methods.But it is prone to produce segmentation errors and shrinking bias phenomena when the color of foreground and background is similar and its interaction efficiency is not high due to pixel-based calculation.To improve these problems,an algorithm combining CS-LBP texture features was proposed in this paper.First the mean shift algorithm is applied to pre-segment the original image into regions to construct region adjacency graph.Then cumulative histogram and CS-LBP texture descriptor are used to extract color and texture features form each region.A new term of texture constraint is added to the energy function and local adaptive regularization parameter is used.So the segmentation effect and shrinking bias phenomenon are improved efficiently.The experiments show that interactivity efficiency and segmentation accuracy are improved.