Application Of Image Segmentation Based On Membrane Computing And Graph Theory

Image segmentation is a key technology from image processing to image analysis and understanding,and is one of the basic problems in low-level vision in the field of computer vision.It divides the image into several regions and extracts the object of interest to facilitate the understanding of the content of the image or the processing of the image information.At present,a large number of image segmentation algorithms have been put forward and widely applied in various fields,such as meteorology cloud pictures analysis,traffic image analysis,medical image analysis,military research and so on.Graph theory is a branch of applied mathematics.Its main research object is graph.Because of the good mapping relationship between graph and image,image segmentation algorithm based on graph theory has attracted much attention in recent years.The main idea is to map the image into a weighted undirected graph.The pixels of the image are mapped to the vertices of the graph,and the similarity or difference between adjacent pixels correspond to the weights of the edges.Then,to complete the image segmentation,the knowledge of graph theory is applied to graph division.The advantages of this method include the balance of global information and local features,the applicability of the wider range and so on,but the disadvantage is the poor real-time performance and so on.Membrane computing is a new branch of bionic natural computing,and it is a new parallel computing model(also called P system).It is abstracted from the structure and function of living cells,the communication and coordination of tissues,organs and cell populations,and the way in which materials are processed in cell structures.It has the advantages of non deterministic,distributed and maximal parallelism.This paper applies the cell-like P system to image segmentation based on graph theory to improve the efficiency of image segmentation based on graph theory.The main research contributions are reflected in the following three aspects。(1)The basic method and implementation of existing graph theory in image processing are studied,an image segmentation algorithm based on membranecalculation and graph theory are designed,which includes the parameter selection of the mapping of image to graph and the method of edge weight calculation.(2)The construction,rules and applications of existing membrane computing models are studied.Then the rules and transmission mechanisms that are consistent with the algorithm are designed to lay the foundation for the specific implementation of the P system.(3)The method,strategy and implementation of the existing P system are studied and analyzed,and the simulator(P system)suitable for the method is designed and implemented.The simulator is applied to specific image segmentation to complete the experimental simulation of image segmentation.In summary,the membrane computing is applied to image segmentation based on graph theory,which improves the efficiency of image segmentation based on graph theory.The designed simulator extends the application of membrane computing in image segmentation,and also provides solutions to solve similar problems in other fields.