Content-based image retrieval (CBIR) uses features that can be extracted from the images themselves. In previous work we have shown that using more than one representation of the images in a collection can improve the results presented to a user without changing the underlying feature extraction or search technologies[4]. In this paper we show that we can also merge the results of multiple CBIR...

Content-based image retrieval (CBIR) is a technique used for extracting similar images from an image database. CBIR system is required to access images effectively and efficiently using information contained in image databases. Here, K-Means is to be used for Image retrieval. The Kmeans method can be applied only in those cases when the mean of a cluster is defined. The K-means method is not su...

In order to bridge the “Semantic gap”, a number of relevance feedback (RF) mechanisms have been applied to content-based image retrieval (CBIR). However current RF techniques in most existing CBIR systems still lack satisfactory user interaction although some work has been done to improve the interaction as well as the search accuracy. In this paper, we propose a four-factor user interaction mo...

Image collections are growing at a rapid rate, motivating the need for efficient and effective tools to query these databases. Contentbased image retrieval (CBIR) techniques extract features directly from image data and use these, coupled with a similarity measure, to search through image collections. In this paper, we introduce some of the basic image features that are used for CBIR.

At present a great deal of research is being done in different aspects of Content-Based Image Retrieval (CBIR). Image classification is one of the most important tasks in image retrieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goa...

Content-Based Image Retrieval (CBIR) is a field of rising interest for the application in Computer-Aided Diagnosis (CADx). Exploiting the visual information hidden in the images for retrieval, it facilitates the identification of similar past examinations, thereby providing a second opinion. Still, CBIR is not an integral part of a radiologist’s daily work. A comprehensive representation of CBI...