Using multi-layer random walker for image segmentation
Minjun Sung, Long-Wen Chang · 2018 International Workshop on Advanced Image Technology (IWAIT) · 2018
Image segmentation can be considered as a label decision problem which assign different labels to every pixel according to its features. In this paper, we propose a supervised and interactive image segmentation algorithm. In our approach, we construct a new graph model which consists of a super-pixel layer and a high order layer. The super-pixel layer is composed by over-segmentation regions called superpixels and the high-order layer is generated by combining edge detection and these over-segmentation regions. Then we construct a graph model and use a random walk algorithm to find the maximum probability label value for each superpixel. The proposed method shows very satisfactory results for some natural images.