A novel method for query based image retrieval using prototype based clustering

Abstract

Content-based image retrieval is a process applied for searching of images from a large database in which searching is done based on the content of the image. The content of the image can be of colour, texture, and shape. This paper concentrates the primitive feature of texture in which the extraction of image content is considered. The implementation of such a system requires the extraction and storing of the image features to be compared with the features of the query image with this flow, the implementation process is more dynamic since all features have already been stored somewhere. This paper proposed a new method called prototype based cluster (PBC) where the features with similar values or properties are grouped together to form clusters and comparison is made between these clusters with the database images and the relevant images are retrieved and stored. This method will show good performance when compared with existing ones. The experimental result shows the effectiveness of our proposed method PBC applied on the query image.