Content-Based Image Retrieval of Fuzzy Database Management Systems

Pages:165-167
Swati Garg (Department of Computer Science, CMJ University, Shillong, Meghalaya)

This study deals with designing a flexible feature space for Content Based Image retrieval Systems (CBIR). For this purpose, initially, a large variety of features are extracted from the regions of the pre-segmented images. Then, the feature set of each object class is learned using the Fuzzy Art Map Architecture, by identifying the weights of each feature for each object class. In the proposed approach the color feature is used and uses the fuzzy c-means clustering algorithm. The database consists of 8 bit bmp format images of 256×256 size. The Hue Saturation Value color space is used. The color Histogram of each image in the database and the query image is obtained & then Median Filtering is applied to reduce the noise. The Fuzzy C-Means Clustering can used to obtain the more features of the images and to improve retrieval efficiency. The similarity between the query image and the images in the database is done using Quadratic Distance approach and the minimum distance image is retrieved from the database.