Nowadays, more and more images are available. However, to find a required image for an
ordinary user is a challenging task. Large amount of researches on image retrieval have …

This paper presents an overview of the ImageCLEF 2014 evaluation lab. Since its first
edition in 2003, ImageCLEF has become one of the key initiatives promoting the benchmark …

In order to improve the retrieval accuracy of content-based image retrieval systems, research
focus has been shifted from designing sophisticated low-level feature extraction algorithms …

This paper presents a method to extract color and texture features of an image quickly for
content-based image retrieval (CBIR). First, HSV color space is quantified rationally. Color …

Semantic-based image retrieval has attracted great interest in recent years. This paper
proposes a region-based image retrieval system with high-level semantic learning. The key …

Digital photographs and visual data have become increasingly available, especially on the
Web considered as the largest image database to date. However, the value of multimedia …

The advancements in the multimedia technologies result in the growth of the image
databases. To retrieve images from such image databases using visual attributes of the …

The collection of digital images is growing at ever-increasing rate which rises the interest of
mining the embedded information. The appropriate representation of an image is …

In this paper, we propose a novel color image retrieval approach by using an effective fusion
of two types of histograms extracted from color and local directional pattern (LDP) …

The main problem in content-based image retrieval (CBIR) systems is the semantic gap
which needs to be reduced for efficient retrieval. The common imaging signs (CISs) which …