Research On Image Segmentation Based On Improved Fuzzy C-means Algorithm

Image segmentation is a technique and process that divides an image into characteristic regions.It is the basis for analyzing and understanding the image.It can make the images have their own characteristics and has a very impor-tant position in image engineering.The knowledge of fuzzy theory has a good explanation for the uncertainty of image segmentation.Therefore,the image seg-mentation of fuzzy clustering has been widely studied and applied in recent years.The main work of this paper is on the basis of the existing fuzzy clustering algorithm,and discusses the problem of improved image clustering and segmen-tation using fuzzy C-means clustering.The full text is divided into five chapters:In Chapter 1,introduces the research background and significance of this pa-per,image segmentation and the research status of fuzzy C-mean clustering algo-rithm at home and abroad.In Chapter 2,introduces the basic concepts and theoretical basis of hard C-mean clustering,fuzzy C-mean clustering,improved fuzzy C-mean clustering and entropy C-means clustering.In Chapter 3,based on the theory of fuzzy C-means clustering,an improved fuzzy C-means clustering algorithm is presented.The computational process and concrete implementation steps of the MPCM algorithm are given.The experi-mental results show that MPCM Clearer data points and image clustering.In Chapter 4,proposes a new fuzzy C-means clustering IMPCM method and proves its convergence.The application of IMPCM algorithm in image cluster-ing segmentation is discussed.Through experiments,it has been found that the IMPCM algorithm shortens the running time compared to the IPCM1 algorithm and improves the accuracy of the image segmentation effect.In Chapter 5,the paper summarizes the content of this article,explains the advantages and disadvantages of the algorithm,and looks forward to the follow-up research.The algorithm of this paper is based on IPCM1.It points out that the IPCM1 algorithm is not very effective in noise processing and the accuracy of image seg-mentation is not high enough.The IPCM1 algorithm has been improved,the MPCM and IMPCM algorithm has been proposed.Experimental results show that the proposed algorithm is superior to other methods in image segmentation accuracy and improves the robustness of the algorithm.In noise image segmen-tation,noise interference is better suppressed.The cluster segmentation results proposed in this paper are closer to people's visual effects,so the algorithm of this paper has better universality than the IPCM1 algorithm.