Effectiveness Analysis Of Fuzzy Clustering And Research On Image Segmentation

With the rapid development of science,the information age brings more and more data to people.Now there are a lot of underutilized data in all walks of life.In order to make full use of the information brought by the data,it is necessary to process and analyze the data.Firstly,this paper analyzes the validity index of fuzzy clustering,and proposes a new validity index of fuzzy clustering.Clustering and fuzzy clustering are good methods for data classification,which can make people understand data more clearly.The effectiveness of clustering and fuzzy clustering directly affects the clustering effect.In this paper,the validity of clustering is analyzed firstly.Then,based on the inner compactness and the separation between clusters of fuzzy clustering,a new fuzzy clustering evaluation index is proposed by considering many factors such as the geometric structure characteristics of data set and the size of the cluster,and a corresponding fuzzy clustering algorithm is proposed according to the fuzzy clustering evaluation index.Secondly,this paper improves the threshold segmentation algorithm in image segmentation technology,and proposes a new image threshold segmentation algorithm based on fuzzy mathematics.There are many image data in reality.Image segmentation technology is one of the necessary technologies to process image data.It has been widely used in computer vision,pattern recognition,medical image processing and other scenes.In this paper,based on the fuzzy similarity method in fuzzy mathematics,a new image membership function is obtained by combining the pixel relationship and spatial relationship,and then the best threshold value of image segmentation is obtained by the correlation coefficient method in fuzzy mathematics.Finally,the image is divided into two parts by the best threshold value to achieve image segmentation.This new algorithm improves the previous algorithm and achieves better image segmentation results.Finally,the effectiveness index of fuzzy clustering and the new image segmentation algorithm are compared.Through comparative experiments,we can see that the fuzzy clustering validity index proposed in this paper is better than other clustering validity indexes to some extent,and the image segmentation algorithm proposed in this paper is also better than the previous methods.At the end of this paper,the shortcomings of the methods proposed in this paper are also analyzed,and the direction for improvement in the future is proposed.