Integrating Fuzzy C-Means Clustering Technique with K-Means Clustering Technique for CBIR

Image database sizes have increased enormously in the recent years due to the development of the technology which has developed the need for Content Based Image Retrieval (CBIR) system. In this study a CBIR system that allows searching and retrieves images from the databases is developed using the fuzzy c-means algorithm and K-means clustering, the system uses the low level features like color, texture and shape. Feature extractions are done using the space transformations and median filtering and then color feature extractions are done using the fuzzy methods to represent color in a way that reduces this semantic gap. Fuzzy c-means clustering is first applied for grouping similar images and k-means clustering technique is then applied to retrieve a better favored images.