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...

Most Content-Based Image Retrieval (CBIR) systems employ color as primary feature with texture and shape as secondary features. Very few systems exploit spatial features. None of the available systems combines all three visual features, texture, shape and location, for organization and retrieval. Moreover relatively few systems use Gabor filters in texture extraction, despite the widely acclaim...

The main goal of content based image retrieval is to e ciently retrieve images that are visually sim ilar to a query image In this paper we will focus on content based image retrieval from large medi cal databases outline the problems speci c in this area and describe the recent advances in the eld We will also present some of the more signi cant re sults obtained with ASSERT Automatic Search a...

This paper presents a content-based image retrieval system for aggregation and combination of different image features. Feature aggregation is important technique in general content-based image retrieval systems that employ multiple visual features to characterize image content. We introduced and evaluated linear combination to fuse different features. The most important step in the feature agg...

This paper provides a formal speciication for concept-based image retrieval using triples. To eeectively manage a vast amount of images, we may need an image retrieval systems capable of indexing and searching images based on the characteristics of their content. However, such a content-based image retrieval technique alone may not satisfy user queries if retrieved images turn out to be relevan...

A feasibility study for a new method for content based image retrieval is presented. First, an image representation using multiscale top points is introduced. This representation is validated using a minimal variance reconstruction algorithm. The image retrieval problem can now be translated into comparing distances between point sets. For this purpose the proportional transportation distance (...

The existing multi-dimensional index structures are not adequate for indexing higherdimensional data sets. Although conceptually they can be extended to higher dimensionalities, they usually require time and space that grow exponentially with the dimensionality. In this paper, we analyze the existing index structures and derive some requirements of an index structure for content-based image ret...