An Image Retrieval Method Based on Content Self-Organized and Interactive

Abstract

How to find the image we need expediently in the tremendous database is one of the most important issues in content-based image retrieval (CBIR). In this paper, we presented an image retrieval system based on image content using fuzzy logic and proposed a new concept on partition the entire database based on content self-organized. In detail, we used modified fuzzy c-means (MFCM) clustering scheme to cluster the database before retrieval and defined a new method to determine the fuzzy weight. To improve the retrieval effectiveness more, this paper also used interactive query (IQ) and presented a new relevance feedback (RF) framework. On all accounts, we designed and implemented a content-based self-organized and interactive retrieval system. Experiments show that it contributes to improving retrieval effectiveness and will be applied in the E-government.