Tissue-like P system for Segmentation of 2D Hexagonal Images

Membrane computing, which is a new computational model inspired by the structure and functioning of biological cells and by the way the cells are organized in tissues. MC has been adopted in many real world applications including image segmentation. In contrast to the traditional square grid for representing and sampling digital images, hexagonal grid is an alternative efficient mechanism which can better represents and visualizes the curved objects. In this paper, a tissue-like P system with region-based and edge-based segmentation is used to segment two dimensional hexagonal images, wherein P-Lingua programming language is used to implement and validate the proposed system. The achieved experimental results clearly demonstrated the effectiveness of using hexagonal connectivity to segment two dimensional images in a less number of rules and computational steps. Moreover, the results reveal that this approach has the potential of segmenting large images in few number of steps.