Image Segmentation Based on the Fuzzy Clustering Algorithm using Average Intracluster Distance

Abstract

Image Segmentation Based on the Fuzzy Clustering Algorithm using Average Intracluster Distance Image segmentation is one of the important processes in the image information extraction for computer vision systems. The fuzzy clustering methods have been extensively used in the image segmentation because it extract feature information of the region. Most of fuzzy clustering methods have used the Fuzzy C-means(FCM) algorithm. This algorithm can be misclassified about the different size of cluster because the degree of membership depends on highly the distance between data and the centroids of the clusters. This paper proposes a fuzzy clustering algorithm using the Average Intracluster Distance that classifies data uniformly without regard to the size of data sets. The Average Intracluster Distance take an average of the vector set belong to each cluster and increase in exact propotion to it's size and density. The experimental results demonstrate that the proposed approach has the good classication entropy and validity function