Frequential and color analysis for hair mask segmentation

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 positions are initialized from the fusion of frequential and color masks. At the end the matting treatment result is use to segment the hair. Results are evaluated using semi- manual segmentation references.