An Image Segmentation Algorithm Based on Graph Theory

It is difficult to determine the threshold and weight coefficients in image segmentation.Aiming at this problem,this paper proposes a new image segmentation algorithm based on graph theory.It uses two-dimensional Gaussian distribution function as the edge weight coefficient for it is dynamic adaptive,as well as resorts the regional-regional and inter-regional similarity function to delimit the gap function,and finds a dynamics determine function for the area to be merged or segmented.Experimental results show that this algorithm is better than other similar ones in image segmentation,and it can save the running time.