A Novel Graph Structure with Excluded Seed Regions and Expanded Adjacent Nodes for Image Segmentation via Graph Cut - Kondo, Noriya; Sato, Masatoshi; Otake, Tsuyoshi (Journal of Signal Processing, 2024)
In this paper, we propose a novel graph structure with excluded seed regions and expanded adjacent nodes for image segmentation via Graph Cut. Graph Cut is one of the most effective image segmentation methods. The computational complexity of Graph Cut is known as O(n2log n). In the conventional method, since n is the total number of input image pixels, the larger the image size, the longer the computation time. In our previous study, accelerated Graph Cut by excluding seed region from graph structure was proposed. Our previous study has reduced the number of n and accelerated computation time. However, the challenge of accuracy remains. In this study, we expanded adjacent nodes to improve accuracy. According to the simulations, the proposed method achieved accurate results compared to conventional method.