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Image database organization based on membership values and connectivity graph

A fast, simple and low complexity technique for image database organization is presented. The basic idea is to reveal the connectivity relations of the database obtain information of the database structure and facilitate the clustering process. This is achieved by randomly selecting a certain number of prototype data and using appropriately the membership values of the rest data points to the selected prototypes. The clustering is easily performed in the final step by using graph theory methodology.