Imaga Segmentation Method Based On Graph Cut Combining Minimum Spanning Tree

Image segmentation is the most critical step in image processing.Graph plotting is an image segmentation method based on graph theory.It has the support of graph theo ry.The image segmentation method based on graph cut can take into account the local and global features of the image,which has attracted the attention of scholars in recent years.With the development of science and technology,the image resolution is high a nd the actual application requirements are high as well,making the traditional graph-c utting method unable to meet the actual application requirements.For the traditional gr aph-cutting image segmentation method,the efficiency is low and the segmentation ac curacy is not high.This paper presents a segmentation method based on minimum spa nning tree.The main work of this paper has the following two points.Firstly,the traditional graph-cutting method does not fully consider the situation t hat adjacent pixels may belong to different classes.In the construction of the energy fu nction,we consider that the original two adjacent nodes may not be adjacent to each ot her in the minimum spanning tree.For this non-adjacent case,we re-determine the cal culation method for the weights of the edges in the graph.The construction of the grap h is more accurate,thereby improving the segmentation accuracy of the algorithm.Secondly,in the process of implementing the former method,we found that the al gorithm's accuracy is improved and the complexity of the algorithm is also increased.I n order to reduce the complexity of the algorithm,we use the method of minimum spa nning tree decomposition to preprocess the image to reduce it.The number of nodes in the graph increases the efficiency of the algorithm.The experimental results show that the proposed method has a better effect on the accuracy and efficiency of segmentatio n than the existing graph segmentation methods.