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Frequential and color analysis for hair mask segmentation

Abstract : In this paper, we present an automatic method for hair segmentation. Our algorithm is divided into two steps. Firstly, we take information from frequential and color analysis in order to create binary masks as descriptor of the hair location. Secondly, we perform a ‘matting treatment' which is a process to extract foreground object from an image. This approach is based on markers which are initialized from the fusion of frequential and color masks. At the end of this process, we segment the hair from the matting treatment result. Results are evaluated using semi-manual segmentation references.
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Contributor : Cedric Rousset <>
Submitted on : Thursday, September 18, 2008 - 2:52:59 PM
Last modification on : Thursday, November 19, 2020 - 1:00:53 PM
Long-term archiving on: : Thursday, June 3, 2010 - 9:44:24 PM


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  • HAL Id : hal-00322719, version 1



Cedric Rousset, Pierre-Yves Coulon. Frequential and color analysis for hair mask segmentation. 15th IEEE International Conference on Image Processing (ICIP 2008), Oct 2008, San Diego, United States. pp.2276. ⟨hal-00322719⟩



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