An Image Segmentation Method by Combining Fuzzy C-Means Clustering and Graph Cuts Optimization for Multiphase Level Set Algorithms

Multiphase level set model is sensitive to initial contour curve and has huge computation in the process of the multiple objects´ segmentation. This paper presents a novel Image segmentation method for multiphase scenario, which initialize the multiphase level set function by coarse image segmentation using fuzzy C-means clustering algorithm and apply graph cut algorithm to acquire multiphase output image. The method effectively reduces the sensitivity of the multiphase level set algorithm to initial contour and is easier to gain the multiphase output image by graph cut algorithm. At the same time, because of using the graph cut algorithm, the multiphase level set function quickly converge to the minimum energy value with small amount of calculation and high computational efficiency. The experiments show that this method has better segmentation effect and higher efficiency of image segmentation.