15 November 2007 Automatic framework for highly efficient natural image matting
Author Affiliations +
Proceedings Volume 6787, MIPPR 2007: Multispectral Image Processing; 67872D (2007); doi: 10.1117/12.752763
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Traditional image matting approaches requires user interaction. This paper proposes an automatic framework for natural image matting. The method seamlessly incorporates image matting with the top-down process of segmentation by weighted aggregation to get a rich and multi-scale grapy pyramid representation of the input image. Using the coupling between aggregates in the graph pyramid, the region for matting is detected adaptively and automatically. Meanwhile, foreground and background regions are determined with state variables. An energy function is constructed to represent the similarity and smoothness properties of a matte and is iteratively optimized. Under the automatic matting framework, color sampling is more accurate than existing methods since multi-scale measurements such as intensity and texture are fully considered. Experiments show that the proposed automatic method is more efficient to extract high quality matte even for difficult images in which foreground and background have very similar colors. Another attractive feature of the method is that it can extract mattes for multi-objects at one computing time.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fazhi He, Yue Wu, Dengyi Zhang, Zhiyong Huang, Lingyun Wei, Chunxia Xiao, "Automatic framework for highly efficient natural image matting", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 67872D (15 November 2007); doi: 10.1117/12.752763; https://doi.org/10.1117/12.752763

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