Abstract This article considers the problem of how to formulate a framework for the study of the nearness of tolerance rough sets (TRS). The solution to the problem stems from recent work on near sets and approach spaces as well as from the realisation that disjoint TRSs can be viewed in the context of approach merotopic spaces. A set of TRSs equipped with a distance function satisfying certain...

In content-based image retrieval (CBIR), the user usually poses several labelled images and then the system attempts to retrieve all the images relevant to the target concept defined by these labelled images. It may be helpful if the system can return relevant images where the regions of interest (ROI) are explicitly located. In this paper, this task is accomplished with the help of multi-insta...

In this paper we look at an image retrieval scenario that we call mental image category search, where the user has an image class in his or her mind and wishes to retrieve several such images from a database, without the benefit of an example. We propose a content-based image retrieval system based on Bayesian inference. The approach is evaluated by performing searches for categories of image t...

In this paper we propose to employ human visual attention models for content based image retrieval. This approach is called query by saliency content retrieval (QSCR) and considers visual saliency at both local and global image levels. Each image, from a given database, is segmented and specific features are evaluated locally for each of its regions. The global saliency is evaluated based on ed...

Biorthonormal M-band wavelet transform is used to decompose the image into sub-bands for constructing the feature database in content-based image retrieval of 1856 Brodatz texture images. Texture features are obtained by computing the measure of energy, standard deviation and its combination on each band. Results are far superior and impressive than conventional two-band wavelet decomposition. ...

One of the important parts of learning processing is retrieving images that are related to learning context. The SCORM uses metadata to retrieve various learning content in the e-learning environment. There are some possibilities to make metadata differently depending on individual interpretations even though the content is same because metadata is made manually. This paper proposes a new metho...

In the last decade, the application of content-based image retrieval (CBIR) system has raised in the medical field such as medical imaging, crime prevention. The first content-based image retrieval system was introduced in 1990s. The content-based image retrieval (CBIR) system tried to overcome the problem of retrieving images automatically from a large database based on the different features ...

With the increasing number of stereo images/videos in commercial markets, the demand for content-based image retrieval (CBIR) to deal with stereo media becomes urgent. To meet this demand, a novel framework is proposed where depth cues are extracted from stereo pairs and employed in a re-ranking scheme to refine results from conventional CBIR. Experiments show the proposed method yields promisi...

This letter presents a two-stage statistical approach for “exploring and explaining” a pictorial database, for content-based image retrieval systems. First, we describe how correspondence analysis provides image classes, as well as facilitates the understanding of the role of image primitives and attributes used to index pictures. Such understanding allows an intelligent choice of features, and...

This paper describes a method of introducing spatial consistency constraints in the process of matching set-based descriptors extracted from digital images. The proposed matching technique is guided by a rule that can be summarized as follows: a descriptor is important for the match if it is similar to some descriptor from the other image and its spatial neighbors are important. The resulting m...