Genetic Algorithm Utilizing Image Clustering with Merge and Split Processes Which Allows Minimizing Fisher Distance Between Clusters
نویسنده
چکیده
Genetic algorithm utilizing image clustering with merge and split processes which allows minimizing Fisher distance between clusters is proposed. Through experiments with simulation and real remote sensing satellite imagery data, it is found that the proposed clustering method is superior to the conventional k-means and ISODATA clustering methods in comparison to the geographic maps and classification results from Maximum Likelihood classification method. Keyword—-image clustering; clustering; genetic algorithm; Fisher distance
منابع مشابه
Data Clustring Using A New CGA(Chaotic-Generic Algorithm) Approach
Clustering is the process of dividing a set of input data into a number of subgroups. The members of each subgroup are similar to each other but different from members of other subgroups. The genetic algorithm has enjoyed many applications in clustering data. One of these applications is the clustering of images. The problem with the earlier methods used in clustering images was in selecting in...
متن کاملData Clustring Using A New CGA(Chaotic-Generic Algorithm) Approach
Clustering is the process of dividing a set of input data into a number of subgroups. The members of each subgroup are similar to each other but different from members of other subgroups. The genetic algorithm has enjoyed many applications in clustering data. One of these applications is the clustering of images. The problem with the earlier methods used in clustering images was in selecting in...
متن کاملAutomatic shape independent clustering with global optimum cluster determinations
A new method which allows identifying any shape of cluster patterns in case of numerical clustering is proposed. The method is based on the iterative clustering construction utilizing a nearest neighbor distance between clusters to merge. The method differs from other techniques of which the cluster density is determined based on calculating the variance factors. The cluster density proposed he...
متن کاملComparative Study between the Proposed GA Based ISODAT Clustering and the Conventional Clustering Methods
A method of GA: Genetic Algorithm based ISODATA clustering is proposed.GA clustering is now widely available. One of the problems for GA clustering is a poor clustering performance due to the assumption that clusters are represented as convex functions. Well known ISODATA clustering has parameters of threshold for merge and split. The parameters have to be determined without any assumption (con...
متن کاملComparative study between the proposed shape independent clustering method and the conventional methods(K-means and the other)
Cluster analysis aims at identifying groups of similar objects and, therefore helps to discover distribution of patterns and interesting correlations in the data sets. In this paper, we propose to provide a consistent partitioning of a dataset which allows identifying any shape of cluster patterns in case of numerical clustering, convex or non-convex. The method is based on layered structure re...
متن کامل