Novel segmentation for twig problem by adding prior nodes in Random-Walk algorithm

In object identification image Segmentation is the first step in digital image processing. It can be used to compress different segments or areas of image. A novel sub-Markov Random Walk (subRW) algorithm with label prior is proposed for seeded image segmentation. It is traditional random walker on a graph with added auxiliary nodes. The uniqueness will be nothing but adding or changing the auxiliary nodes in segmentation algorithm. We face segmentation problem in existing system if the image having very thin and elongated parts. we design a new sub RW algorithm with label prior to solve the segmentation problem of objects with thin and elongated parts (i.e Twig Problem). The experimental results on both synthetic and natural images with twigs demonstrate that the proposed subRW method outperforms previous Well Known RW Algorithms for segmentation.