Content-based image retrieval (CBIR) has been widely used in many applications. Large storage and computation overheads have made the outsourcing of CBIR services attractive. However, the privacy issues brought by outsourcing have become a big problem. In this paper, a secure CBIR scheme based on an encrypted difference histogram (EDH-CBIR) is proposed. Firstly, the image owner calculates the o...

There is large amount of digital data floating all over the world today. If we want to search a particular image or file, we get a lot of results. CBIR are the systems which search an image or article on the bases of their content. Therefore, Content-based image retrieval has become one of the most active research areas from last few years. This paper gives a review of features used in content ...

Content based image retrieval (CBIR) has been well studied in the computer vision and multimedia community. Content free image retrieval (CFIR) methods, and their complementary characteristics to CBIR has not received enough attention in the literature. Performance of CBIR is constrained by the semantic gap between the feature representations and user expectations, while CFIR suffers with spars...

Content-based image retrieval (CBIR) is a method for finding similar images from large image databases. As the network and development of multimedia technologies are becoming more popular, users are not satisfied with the traditional information retrieval techniques. In recent years, local descriptors are used as image features to improve the performance of CBIR. The SIFT is one of the most loc...

The paper presents the architecture of experimental Content-Based Image Retrieval (CBIR) system APICAS ("Art Painting Image Colour Aesthetics and Semantics"). This system has been developed within a doctoral thesis which aims to provide a suite of specialized tools for CBIR within a digital library of art images. The main functions in APICAS are: data ingest; visual features extraction; and dat...

Content based image retrieval (CBIR) refers to image content that is retrieved directly, by which the images with features or containing certain contents will be searched in an image database. The main idea of CBIR is to analyze image information by low level features of an image, which includes color, texture, shape and space relationship of objects etc., and to set up feature vectors of an im...

Image content on the Web is increasing exponentially. As a result, there is a need for image retrieval systems. Historically, there have been two methodologies, text-based and content-based. In the text-based approach, query systems retrieve images that have been manually annotated using key words. This approach can be problematic: it is labor-intensive and maybe biased according to the subject...

One of the fundamental issues in bridging the gap between the proliferation of Content-Based Image Retrieval (CBIR) systems in the scientific literature and the deficiency of their usage in medical community is based on the characteristic of CBIR to access information by images or/and text only. Yet, the way physicians are reasoning about patients leads intuitively to a case representation. Hen...

This paper analyzes the similarity measurement in Content-based Image and Video Retrieval systems (CBIR). The goal is to identify preliminaries for successful queries as the basis for the implementation of a query engine in the Content-based Visual Information Retrieval framework (VizIR). VizIR is an open CBIR framework for researchers, software developers and instructors. Past efforts in CBIR ...

| Content-Based Image Retrieval (CBIR) has become one of the most active research areas in the past few years. Many visual feature representations have been explored and many systems built. While these research eeorts establish the basis of CBIR, the usefulness of the proposed approaches is limited. Speciically, these eeorts have relatively ignored two distinct characteristics of CBIR systems: ...